diff --git a/analyses/README.md b/analyses/README.md index 24acee0aaa..f00d67932e 100644 --- a/analyses/README.md +++ b/analyses/README.md @@ -25,7 +25,7 @@ Note that _nearly all_ modules use the harmonized clinical data file (`pbta-hist | [`immune-deconv`](https://github.com/AlexsLemonade/OpenPBTA-analysis/tree/master/analyses/immune-deconv) | `pbta-gene-expression-rsem-fpkm-collapsed.polya.rds`
`pbta-gene-expression-rsem-fpkm-collapsed.stranded.rds` | Immune/Stroma characterization across PBTA (part of [#15](https://github.com/AlexsLemonade/OpenPBTA-analysis/issues/15)) | `results/deconv-output.RData` | [`independent-samples`](https://github.com/AlexsLemonade/OpenPBTA-analysis/tree/master/analyses/independent-samples) | `pbta-histologies.tsv` | Generates independent specimen lists for WGS/WXS samples | `results/independent-specimens.wgs.primary.tsv`
`results/independent-specimens.wgs.primary-plus.tsv`
`results/independent-specimens.wgswxs.primary.tsv`
`results/independent-specimens.wgswxs.primary-plus.tsv` (included in data download) | [`interaction-plots`](https://github.com/AlexsLemonade/OpenPBTA-analysis/tree/master/analyses/interaction-plots) | `independent-specimens.wgs.primary-plus.tsv`
`pbta-snv-consensus-mutation.maf.tsv.gz` | Creates interaction plots for mutation mutual exclusivity/co-occurrence [#13](https://github.com/AlexsLemonade/OpenPBTA-analysis/issues/13); may be updated to include other data types (e.g., fusions) | N/A -| [`molecular-subtyping-ATRT`](https://github.com/AlexsLemonade/OpenPBTA-analysis/tree/master/analyses/molecular-subtyping-ATRT) | `analyses/gene-set-enrichment-analysis/results/gsva_scores_stranded.tsv`
`pbta-gene-expression-rsem-fpkm-collapsed.stranded.rds`
`analyses/focal-cn-file-preparation/results/cnvkit_annotated_cn_autosomes.tsv.gz`
`pbta-snv-consensus-mutation-tmb-all.tsv`
`pbta-cnv-cnvkit-gistic.zip` | *In progress*; summarizing data into tabular format in order to molecularly subtype ATRT samples [#244](https://github.com/AlexsLemonade/OpenPBTA-analysis/issues/244) | N/A +| [`molecular-subtyping-ATRT`](https://github.com/AlexsLemonade/OpenPBTA-analysis/tree/master/analyses/molecular-subtyping-ATRT) | `analyses/gene-set-enrichment-analysis/results/gsva_scores_stranded.tsv`
`pbta-gene-expression-rsem-fpkm-collapsed.stranded.rds`
`analyses/focal-cn-file-preparation/results/consensus_seg_annotated_cn_autosomes.tsv.gz`
`pbta-snv-consensus-mutation-tmb-all.tsv`
`2019-01-28-consensus-cnv.zip` from [#453 (comment)](https://github.com/AlexsLemonade/OpenPBTA-analysis/issues/453#issuecomment-579340618) | Summarizing data into tabular format in order to molecularly subtype ATRT samples [#244](https://github.com/AlexsLemonade/OpenPBTA-analysis/issues/244); this analysis did not work | N/A | [`molecular-subtyping-embryonal`](https://github.com/AlexsLemonade/OpenPBTA-analysis/tree/master/analyses/molecular-subtyping-embryonal) | `fusion_summary_embryonal_foi.tsv`
`pbta-histologies.tsv`
`analyses/focal-cn-file-preparation/cnvkit_annotated_cn_autosomes.tsv.gz`
`analyses/focal-cn-file-preparation/cnvkit_annotated_cn_x_and_y.tsv.gz`
`pbta-gene-expression-rsem-fpkm-collapsed.stranded.rds`
`pbta-gene-expression-rsem-fpkm-collapsed.polya.rds` | *In progress*; molecular subtyping of non-medulloblastoma, non-ATRT embryonal tumors [#251](https://github.com/AlexsLemonade/OpenPBTA-analysis/issues/251) | N/A | [`molecular-subtyping-HGG`](https://github.com/AlexsLemonade/OpenPBTA-analysis/tree/master/analyses/molecular-subtyping-HGG) | `pbta-snv-consensus-mutation.maf.tsv.gz`
`analyses/focal-cn-preparation/results/cnvkit_annotated_cn_autosomes.tsv.gz`
`pbta-fusion-putative-oncogenic.tsv`
`pbta-cnv-cnvkit-gistic.zip`
`pbta-gene-expression-rsem-fpkm-collapsed.stranded.rds`
`pbta-gene-expression-rsem-fpkm-collapsed.polya.rds` | *In progress*; molecular subtyping of high-grade glioma samples [#249](https://github.com/AlexsLemonade/OpenPBTA-analysis/issues/249) | N/A | [`molecular-subtyping-SHH-tp53`](https://github.com/AlexsLemonade/OpenPBTA-analysis/tree/master/analyses/molecular-subtyping-SHH-tp53) | `pbta-histologies`
`pbta-snv-consensus-mutation.maf.tsv.gz` | Identify the SHH-classified medulloblastoma samples that have TP53 mutations | N/A diff --git a/analyses/molecular-subtyping-ATRT/00-subset-files-for-ATRT.R b/analyses/molecular-subtyping-ATRT/00-subset-files-for-ATRT.R index eb7f68b509..55b7eee2d9 100644 --- a/analyses/molecular-subtyping-ATRT/00-subset-files-for-ATRT.R +++ b/analyses/molecular-subtyping-ATRT/00-subset-files-for-ATRT.R @@ -30,6 +30,8 @@ if (!dir.exists(results_dir)) { dir.create(results_dir) } +scratch_dir <- file.path(root_dir, "scratch") + # Read in metadata metadata <- readr::read_tsv(file.path(root_dir, "data", "pbta-histologies.tsv")) @@ -63,15 +65,13 @@ stranded_expression <- ) # Read in focal CN data -## TODO: This section will be updated to read in focal CN data derived from -## copy number consensus calls. cn_df <- readr::read_tsv( file.path( root_dir, "analyses", "focal-cn-file-preparation", "results", - "cnvkit_annotated_cn_autosomes.tsv.gz" + "consensus_seg_annotated_cn_autosomes.tsv.gz" ) ) @@ -82,15 +82,17 @@ tmb_df <- "pbta-snv-consensus-mutation-tmb-all.tsv")) # Read in GISTIC `broad_values_by_arm.txt` file -gistic_df <- - data.table::fread(unzip( - file.path(root_dir, "data", "pbta-cnv-cnvkit-gistic.zip"), - files = file.path( - "2019-12-10-gistic-results-cnvkit", - "broad_values_by_arm.txt" - ), - exdir = file.path(root_dir, "scratch") - ), data.table = FALSE) +# TODO: update once the consensus GISTIC results are in the data release +download.file(url = "https://github.com/AlexsLemonade/OpenPBTA-analysis/files/4123481/2019-01-28-consensus-cnv.zip", + destfile = file.path(scratch_dir, "2019-01-28-consensus-cnv.zip"), + quiet = TRUE) +unzip(file.path(scratch_dir, "2019-01-28-consensus-cnv.zip"), + exdir = file.path(scratch_dir, "2019-01-28-consensus-cnv"), + files = file.path("2019-01-28-consensus-cnv", "broad_values_by_arm.txt")) +gistic_df <- data.table::fread(file.path(scratch_dir, + "2019-01-28-consensus-cnv", + "broad_values_by_arm.txt"), + data.table = FALSE) #### Filter metadata ----------------------------------------------------------- diff --git a/analyses/molecular-subtyping-ATRT/01-ATRT-molecular-subtyping-data-prep.Rmd b/analyses/molecular-subtyping-ATRT/01-ATRT-molecular-subtyping-data-prep.Rmd index e58bf6e829..08dd32b1be 100644 --- a/analyses/molecular-subtyping-ATRT/01-ATRT-molecular-subtyping-data-prep.Rmd +++ b/analyses/molecular-subtyping-ATRT/01-ATRT-molecular-subtyping-data-prep.Rmd @@ -198,6 +198,7 @@ collapsed_metadata %>% ```{r} # Define target overexpressed gene vectors +# https://github.com/AlexsLemonade/OpenPBTA-analysis/issues/244#issuecomment-576850172 tyr_genes <- c("TYR", "MITF", @@ -205,44 +206,29 @@ tyr_genes <- "VEGFA", "DNAH11", "SPEF1", - "POU3F4", - "POU3F2", - "PBX1") + "MSX2", + "STAT3", + "PRRX1", + "LMX1", + "OTX2") shh_genes <- c( "MYCN", "GLI2", "CDK6", "ASCL1", - "HES5/6", - "DLL1/3", - "ZBTB7A", - "RXF3", - "RXF2", - "MYBL2", - "MXI1", - "MEIS3", - "MEIS2", - "MAX", - "INSM1", - "FOXK1" + "HES5", + "HES6", + "DLL1", + "DLL3", + "LHX2", + "TEAD1" ) myc_genes <- c( "MYC", "HOTAIR", - "HOX", - "TCF7L2", - "STAT1", - "REST", - "RARG", - "RAD21", - "NR4A2", - "IRF9", - "IRF8", - "FOXC1", - "CEBPB", - "ATF4" + "TEAD3" ) # Filter to only the genes of interest @@ -394,6 +380,12 @@ rm(gistic_df, atrt_expression_cn_tmb_df) # Save final table of results ```{r} +# For reordering the output, we will use the vector of genes as input but we +# need to account for genes that are missing from the expression matrix +tyr_genes <- intersect(colnames(final_df), tyr_genes) +shh_genes <- intersect(colnames(final_df), shh_genes) +myc_genes <- intersect(colnames(final_df), myc_genes) + # Save final data.frame final_df <- final_df %>% dplyr::select( @@ -407,31 +399,13 @@ final_df <- final_df %>% location_summary, chr_22q_loss, SMARCB1_focal_status, - TYR, - MITF, - DCT, - VEGFA, - DNAH11, - SPEF1, - POU3F4, - POU3F2, - PBX1, + !!! rlang::syms(tyr_genes), SMARCA4_focal_status, HALLMARK_NOTCH_SIGNALING, - MYCN, - GLI2, - CDK6, - ASCL1, - ZBTB7A, - MYBL2, - MXI1, - MEIS3, - MEIS2, - MAX, - INSM1, - FOXK1, + !!! rlang::syms(shh_genes), HALLMARK_MYC_TARGETS_V1, HALLMARK_MYC_TARGETS_V2, + !!! rlang::syms(myc_genes), dplyr::everything() ) diff --git a/analyses/molecular-subtyping-ATRT/01-ATRT-molecular-subtyping-data-prep.nb.html b/analyses/molecular-subtyping-ATRT/01-ATRT-molecular-subtyping-data-prep.nb.html index dc1e690e98..ab013fadd2 100644 --- a/analyses/molecular-subtyping-ATRT/01-ATRT-molecular-subtyping-data-prep.nb.html +++ b/analyses/molecular-subtyping-ATRT/01-ATRT-molecular-subtyping-data-prep.nb.html @@ -5800,7 +5800,7 @@

Usage

Set Up

- +
# Get `magrittr` pipe
 `%>%` <- dplyr::`%>%`
 
@@ -5818,7 +5818,7 @@ 

Set Up

Directories and Files

- +
# Detect the ".git" folder -- this will in the project root directory.
 # Use this as the root directory to ensure proper sourcing of functions no
 # matter where this is called from
@@ -5839,19 +5839,23 @@ 

Directories and Files

# Read in non-subsetted metadata metadata <- readr::read_tsv(file.path(root_dir, "data", "pbta-histologies.tsv"))
- +
Parsed with column specification:
 cols(
   .default = col_character(),
-  OS_days = col_double(),
-  age_last_update_days = col_double(),
-  normal_fraction = col_double(),
-  tumor_fraction = col_double(),
-  tumor_ploidy = col_double(),
-  molecular_subtype = col_logical()
-)
-See spec(...) for full column specifications.
-221 parsing failures.
+  OS_days = col_double(),
+  age_last_update_days = col_double(),
+  normal_fraction = col_double(),
+  tumor_fraction = col_double(),
+  tumor_ploidy = col_double(),
+  molecular_subtype = col_logical()
+)
+ + +
See spec(...) for full column specifications.
+ + +
Warning: 221 parsing failures.
  row               col           expected actual                                                file
 2606 molecular_subtype 1/0/T/F/TRUE/FALSE Group3 '/home/rstudio/kitematic/data/pbta-histologies.tsv'
 2607 molecular_subtype 1/0/T/F/TRUE/FALSE Group4 '/home/rstudio/kitematic/data/pbta-histologies.tsv'
@@ -5860,8 +5864,8 @@ 

Directories and Files

2610 molecular_subtype 1/0/T/F/TRUE/FALSE Group3 '/home/rstudio/kitematic/data/pbta-histologies.tsv' .... ................. .................. ...... ................................................... See problems(...) for more details.
- - + +
# Read in ATRT subset metadata
 subset_metadata <- metadata %>%
   dplyr::filter(short_histology == "ATRT",
@@ -5877,16 +5881,16 @@ 

Directories and Files

gsva_subset <- as.data.frame(readr::read_tsv(file.path(input_dir, "atrt_gsva.tsv")))
- +
Parsed with column specification:
 cols(
-  Kids_First_Biospecimen_ID = col_character(),
-  hallmark_name = col_character(),
-  gsea_score = col_double(),
-  sample_id = col_character()
+  Kids_First_Biospecimen_ID = col_character(),
+  hallmark_name = col_character(),
+  gsea_score = col_double(),
+  sample_id = col_character()
 )
- - + +
# Read in ATRT subset z-scored RNA expression data
 stranded_expression <-
   readr::read_rds(
@@ -5904,17 +5908,17 @@ 

Directories and Files

) )
- +
Parsed with column specification:
 cols(
-  gene_symbol = col_character(),
-  sample_id = col_character(),
-  Kids_First_Participant_ID = col_character(),
-  biospecimen_id = col_character(),
-  status = col_character()
+  gene_symbol = col_character(),
+  sample_id = col_character(),
+  Kids_First_Participant_ID = col_character(),
+  biospecimen_id = col_character(),
+  status = col_character()
 )
- - + +
# Read in ATRT subset consensus mutation data
 tmb_df <-
   data.table::fread(file.path(input_dir,
@@ -5924,14 +5928,14 @@ 

Directories and Files

gistic_df <- readr::read_tsv(file.path(input_dir, "atrt_gistic_broad_values.tsv"))
- +
Parsed with column specification:
 cols(
-  sample_id = col_character(),
-  Kids_First_Biospecimen_ID = col_character(),
-  `22q` = col_double()
+  sample_id = col_character(),
+  Kids_First_Biospecimen_ID = col_character(),
+  `22q` = col_double()
 )
- + @@ -5939,7 +5943,7 @@

Directories and Files

Custom Function

- +
# Custom datatable function
 # Function code adapted from: https://github.com/AlexsLemonade/OpenPBTA-analysis/blob/49acc98f5ffd86853fc70f220623311e13e3ca9f/analyses/collapse-rnaseq/02-analyze-drops.Rmd#L23
 viewDataTable <- function(data) {
@@ -5973,7 +5977,7 @@ 

Prepare Data

Metadata

- +
# Define regions of the brain (using Anatomy of the Brain figure found at
 # https://www.ncbi.nlm.nih.gov/books/NBK65903/figure/CDR0000574573__205/)
 supratentorial <-
@@ -6035,13 +6039,11 @@ 

Metadata

collapsed_metadata %>% head(n = 15)
-
- @@ -6051,8 +6053,9 @@

Filter and join RNA expression, CN, TMB, ssGSVA and GISTIC data

RNA expression data

- +
# Define target overexpressed gene vectors
+# https://github.com/AlexsLemonade/OpenPBTA-analysis/issues/244#issuecomment-576850172
 tyr_genes <-
   c("TYR",
     "MITF",
@@ -6060,44 +6063,29 @@ 

RNA expression data

"VEGFA", "DNAH11", "SPEF1", - "POU3F4", - "POU3F2", - "PBX1") + "MSX2", + "STAT3", + "PRRX1", + "LMX1", + "OTX2") shh_genes <- c( "MYCN", "GLI2", "CDK6", "ASCL1", - "HES5/6", - "DLL1/3", - "ZBTB7A", - "RXF3", - "RXF2", - "MYBL2", - "MXI1", - "MEIS3", - "MEIS2", - "MAX", - "INSM1", - "FOXK1" + "HES5", + "HES6", + "DLL1", + "DLL3", + "LHX2", + "TEAD1" ) myc_genes <- c( "MYC", "HOTAIR", - "HOX", - "TCF7L2", - "STAT1", - "REST", - "RARG", - "RAD21", - "NR4A2", - "IRF9", - "IRF8", - "FOXC1", - "CEBPB", - "ATF4" + "TEAD3" ) # Filter to only the genes of interest @@ -6121,16 +6109,13 @@

RNA expression data

expression_metadata %>% head(n = 15)
-
- - -

-# Join expression data with metadata filtered for `ATRT`
+
+
# Join expression data with metadata filtered for `ATRT`
 atrt_expression_df <- collapsed_metadata %>%
   dplyr::left_join(expression_metadata,
                    by = "sample_id")
@@ -6145,7 +6130,7 @@ 

RNA expression data

CN data

- +
# Filter focal CN data for SMARCB1 and SMARCA4 status
 genes_cn_df <- cn_df %>%
   dplyr::filter(gene_symbol %in% c("SMARCB1", "SMARCA4")) %>%
@@ -6171,16 +6156,13 @@ 

CN data

genes_cn_df %>% head(n = 15)
-
- - -

-# Join ATRT expression data with focal CN data
+
+
# Join ATRT expression data with focal CN data
 atrt_expression_cn_df <- atrt_expression_df %>%
   dplyr::left_join(dplyr::select(genes_cn_df,
                                  -biospecimen_id,
@@ -6197,7 +6179,7 @@ 

CN data

GSVA data

- +
# Filter to only the hallmark gene sets that were named in the issue
 relevant_genesets <- c("HALLMARK_MYC_TARGETS_V1",
                        "HALLMARK_MYC_TARGETS_V2",
@@ -6221,16 +6203,13 @@ 

GSVA data

scaled_gsva %>% head(n = 15)
-
- - -

-# Join ATRT expression and focal CN data with GSVA data
+
+
# Join ATRT expression and focal CN data with GSVA data
 atrt_expression_cn_df <- atrt_expression_cn_df %>%
   dplyr::left_join(scaled_gsva,
                    by = "sample_id")
@@ -6245,21 +6224,18 @@ 

GSVA data

Tumor mutation burden data

- +
# Display `tmb_df`
 tmb_df %>%
   head(n = 15)
-
- - -

-# Join ATRT expression, focal CN data and transposed ssGSEA data with tumor
+
+
# Join ATRT expression, focal CN data and transposed ssGSEA data with tumor
 # mutation burden data
 atrt_expression_cn_tmb_df <- atrt_expression_cn_df %>%
   dplyr::left_join(dplyr::select(tmb_df,
@@ -6277,7 +6253,7 @@ 

Tumor mutation burden data

GISTIC data

- +
gistic_df <- gistic_df %>%
   dplyr::select(-Kids_First_Biospecimen_ID) %>%
   dplyr::group_by(sample_id) %>%
@@ -6289,16 +6265,13 @@ 

GISTIC data

gistic_df %>% head(n = 15)
-
- - -

-# Join GISTIC data with the running final data.frame
+
+
# Join GISTIC data with the running final data.frame
 final_df <- atrt_expression_cn_tmb_df %>%
   dplyr::left_join(gistic_df, by = "sample_id") %>%
   dplyr::distinct()
@@ -6315,8 +6288,14 @@ 

GISTIC data

Save final table of results

- -
# Save final data.frame
+
+
# For reordering the output, we will use the vector of genes as input but we 
+# need to account for genes that are missing from the expression matrix
+tyr_genes <- intersect(colnames(final_df), tyr_genes)
+shh_genes <- intersect(colnames(final_df), shh_genes)
+myc_genes <- intersect(colnames(final_df), myc_genes)
+
+# Save final data.frame
 final_df <- final_df %>%
   dplyr::select(
     sample_id,
@@ -6329,31 +6308,13 @@ 

Save final table of results

location_summary, chr_22q_loss, SMARCB1_focal_status, - TYR, - MITF, - DCT, - VEGFA, - DNAH11, - SPEF1, - POU3F4, - POU3F2, - PBX1, + !!! rlang::syms(tyr_genes), SMARCA4_focal_status, HALLMARK_NOTCH_SIGNALING, - MYCN, - GLI2, - CDK6, - ASCL1, - ZBTB7A, - MYBL2, - MXI1, - MEIS3, - MEIS2, - MAX, - INSM1, - FOXK1, + !!! rlang::syms(shh_genes), HALLMARK_MYC_TARGETS_V1, HALLMARK_MYC_TARGETS_V2, + !!! rlang::syms(myc_genes), dplyr::everything() ) @@ -6365,14 +6326,9 @@

Save final table of results

viewDataTable(final_df)
- - - -
- - - - + +
+ @@ -6382,10 +6338,10 @@

Save final table of results

Session Info

- +
sessionInfo()
- +
R version 3.6.0 (2019-04-26)
 Platform: x86_64-pc-linux-gnu (64-bit)
 Running under: Debian GNU/Linux 9 (stretch)
@@ -6405,25 +6361,27 @@ 

Session Info

[1] stats graphics grDevices utils datasets methods base loaded via a namespace (and not attached): - [1] Rcpp_1.0.1 pillar_1.4.2 compiler_3.6.0 later_0.8.0 - [5] base64enc_0.1-3 tools_3.6.0 digest_0.6.20 bit_1.1-14 - [9] jsonlite_1.6 evaluate_0.14 tibble_2.1.3 pkgconfig_2.0.2 -[13] rlang_0.4.0 shiny_1.3.2 rstudioapi_0.10 crosstalk_1.0.0 -[17] yaml_2.2.0 xfun_0.8 stringr_1.4.0 dplyr_0.8.3 -[21] knitr_1.23 htmlwidgets_1.3 hms_0.4.2 rprojroot_1.3-2 -[25] bit64_0.9-7 DT_0.7 tidyselect_0.2.5 glue_1.3.1 -[29] data.table_1.12.2 R6_2.4.0 rmarkdown_1.13 readr_1.3.1 -[33] purrr_0.3.2 tidyr_0.8.3 magrittr_1.5 backports_1.1.4 -[37] promises_1.0.1 htmltools_0.3.6 rsconnect_0.8.13 assertthat_0.2.1 -[41] mime_0.7 xtable_1.8-4 httpuv_1.5.1 stringi_1.4.3 -[45] crayon_1.3.4
+ [1] Rcpp_1.0.1 knitr_1.23 magrittr_1.5 + [4] hms_0.4.2 tidyselect_0.2.5 xtable_1.8-4 + [7] R6_2.4.0 rlang_0.4.0 stringr_1.4.0 +[10] dplyr_0.8.3 tools_3.6.0 DT_0.7 +[13] data.table_1.12.2 xfun_0.8 crosstalk_1.0.0 +[16] htmltools_0.3.6 yaml_2.2.0 assertthat_0.2.1 +[19] digest_0.6.20 rprojroot_1.3-2 tibble_2.1.3 +[22] crayon_1.3.4 shiny_1.3.2 later_0.8.0 +[25] tidyr_0.8.3 purrr_0.3.2 readr_1.3.1 +[28] promises_1.0.1 htmlwidgets_1.3 base64enc_0.1-3 +[31] mime_0.7 glue_1.3.1 evaluate_0.14 +[34] rmarkdown_1.13 stringi_1.4.3 compiler_3.6.0 +[37] pillar_1.4.2 backports_1.1.4 jsonlite_1.6 +[40] httpuv_1.5.1 pkgconfig_2.0.2
-
---
title: "ATRT Molecular Subtyping - Data Prep"
output: 
  html_notebook:
    toc: TRUE
    toc_float: TRUE
author: Chante Bethell for ALSF CCDL
date: 2019
---

This notebook addresses the issue of molecular subtyping ATRT samples. 

# Usage

This notebook is intended to be run via the command line from the top directory
of the repository as follows:

`Rscript -e "rmarkdown::render('analyses/molecular-subtyping-ATRT/01-ATRT-molecular-subtyping-data-prep.Rmd', clean = TRUE)"`

# Set Up

```{r}
# Get `magrittr` pipe
`%>%` <- dplyr::`%>%`

# Install `DT` and `htmlwidgets` packages for displaying tables
if (!("DT" %in% installed.packages())) {
  install.packages("DT")
}
if (!("htmlwidgets" %in% installed.packages())) {
  install.packages("htmlwidgets")
}
```

## Directories and Files

```{r}
# Detect the ".git" folder -- this will in the project root directory.
# Use this as the root directory to ensure proper sourcing of functions no
# matter where this is called from
root_dir <- rprojroot::find_root(rprojroot::has_dir(".git"))

# File path to results directory
input_dir <-
  file.path(root_dir, "analyses", "molecular-subtyping-ATRT", "atrt-subset")

# File path to results directory
results_dir <-
  file.path(root_dir, "analyses", "molecular-subtyping-ATRT", "results")

if (!dir.exists(results_dir)) {
  dir.create(results_dir)
}

# Read in non-subsetted metadata
metadata <- readr::read_tsv(file.path(root_dir, "data", "pbta-histologies.tsv"))

# Read in ATRT subset metadata
subset_metadata <- metadata %>%
  dplyr::filter(short_histology == "ATRT",
                sample_type == "Tumor",
                composition == "Solid Tissue")

# Select wanted columns in metadata for merging and assign to a new object
select_metadata <- metadata %>%
  dplyr::select(sample_id,
                Kids_First_Biospecimen_ID)

# Read in ATRT subset GSVA pathway scores
gsva_subset <-
  as.data.frame(readr::read_tsv(file.path(input_dir, "atrt_gsva.tsv")))

# Read in ATRT subset z-scored RNA expression data
stranded_expression <-
  readr::read_rds(
    file.path(
      input_dir,
      "atrt_log_expression.RDS"
    )
  )

# Read in ATRT subset focal CN data
cn_df <- readr::read_tsv(
  file.path(
    input_dir,
    "atrt_focal_cn.tsv.gz"
  )
)

# Read in ATRT subset consensus mutation data
tmb_df <-
  data.table::fread(file.path(input_dir,
                              "atrt_tmb.tsv"))

# Read in ATRT subset GISTIC data
gistic_df <-
  readr::read_tsv(file.path(input_dir, "atrt_gistic_broad_values.tsv"))

```

## Custom Function

```{r}
# Custom datatable function
# Function code adapted from: https://github.com/AlexsLemonade/OpenPBTA-analysis/blob/49acc98f5ffd86853fc70f220623311e13e3ca9f/analyses/collapse-rnaseq/02-analyze-drops.Rmd#L23
viewDataTable <- function(data) {
  DT::datatable(
    data,
    rownames = FALSE,
    filter = "bottom",
    class = 'cell-border stripe',
    options = list(
      pageLength = 5,
      searchHighlight = TRUE,
      scrollX = TRUE,
      dom = 'tpi',
      initComplete = htmlwidgets::JS(
        "function(settings, json) {",
        "$(this.api().table().header()).css({'background-color':
                                            '#004467', 'color': '#fff'});",
        "}"
      )
    )
  )
}
```

# Prepare Data

## Metadata

```{r}
# Define regions of the brain (using Anatomy of the Brain figure found at
# https://www.ncbi.nlm.nih.gov/books/NBK65903/figure/CDR0000574573__205/)
supratentorial <-
  c(
    "Skull",
    "Thalamus",
    "Temporal Lobe",
    "Frontal Lobe",
    "Parietal Lobe",
    "Cerebrum",
    "Basal Ganglia",
    "Cranial Nerves NOS",
    "Basal Ganglia;Temporal Lobe",
    "Frontal Lobe;Parietal Lobe;Temporal Lobe",
    "Parietal Lobe;Temporal Lobe",
    "Frontal Lobe;Parietal Lobe"
  )

infratentorial <-
  c(
    "Cerebellum/Posterior Fossa",
    "Brain Stem- Pons;Cerebellum/Posterior Fossa",
    "Cerebellum/Posterior Fossa;Other locations NOS",
    "Brain Stem",
    "Brain Stem- Midbrain/Tectum;Ventricles",
    "Cerebellum/Posterior Fossa;Ventricles",
    "Cerebellum/Posterior Fossa;Spinal Cord- Cervical;Spinal Cord- Lumbar/Thecal Sac;Spinal Cord- Thoracic",
    "Other locations NOS;Spinal Cord- Lumbar/Thecal Sac;Spinal Cord- Thoracic;Ventricles"
  )

collapsed_metadata <- subset_metadata %>%
  dplyr::mutate(
    location_summary = dplyr::case_when(
      primary_site %in% infratentorial ~ "infratentorial",
      primary_site %in% supratentorial ~ "supratentorial",
      TRUE ~ "NA"
    ),
    # Convert `OS_days` values to months and assign new values to `OS_months`
    # column
    OS_months = OS_days / (365 / 12)
  ) %>%
  dplyr::select(
    sample_id,
    Kids_First_Biospecimen_ID,
    Kids_First_Participant_ID,
    location_summary,
    age_at_diagnosis_days,
    OS_months,
    germline_sex_estimate,
    primary_site
  ) %>%
  dplyr::group_by(
    sample_id,
    Kids_First_Participant_ID
  ) %>%
  dplyr::summarize_all(function(x) paste(sort(unique(x)), collapse = ", "))

# Display metadata subsetted for ATRT samples
collapsed_metadata %>%
  head(n = 15)
```

## Filter and join RNA expression, CN, TMB, ssGSVA and GISTIC data

### RNA expression data 

```{r}
# Define target overexpressed gene vectors
tyr_genes <-
  c("TYR",
    "MITF",
    "DCT",
    "VEGFA",
    "DNAH11",
    "SPEF1",
    "POU3F4",
    "POU3F2",
    "PBX1")
shh_genes <-
  c(
    "MYCN",
    "GLI2",
    "CDK6",
    "ASCL1",
    "HES5/6",
    "DLL1/3",
    "ZBTB7A",
    "RXF3",
    "RXF2",
    "MYBL2",
    "MXI1",
    "MEIS3",
    "MEIS2",
    "MAX",
    "INSM1",
    "FOXK1"
  )
myc_genes <-
  c(
    "MYC",
    "HOTAIR",
    "HOX",
    "TCF7L2",
    "STAT1",
    "REST",
    "RARG",
    "RAD21",
    "NR4A2",
    "IRF9",
    "IRF8",
    "FOXC1",
    "CEBPB",
    "ATF4"
  )

# Filter to only the genes of interest
filtered_expression <- stranded_expression[which(
   rownames(stranded_expression) %in% c(tyr_genes, shh_genes, myc_genes)
), ]

# scale does column centering, so we transpose first
long_stranded_expression <- scale(t(filtered_expression), 
                                  center = TRUE,
                                  scale = TRUE)

# Merge metadata with expression data
expression_metadata <- long_stranded_expression %>%
  as.data.frame() %>%
  tibble::rownames_to_column("Kids_First_Biospecimen_ID") %>% 
  dplyr::left_join(select_metadata, by = "Kids_First_Biospecimen_ID") %>%
  dplyr::select(-Kids_First_Biospecimen_ID)

# Display `expression_metadata`
expression_metadata %>%
  head(n = 15)

# Join expression data with metadata filtered for `ATRT`
atrt_expression_df <- collapsed_metadata %>%
  dplyr::left_join(expression_metadata,
                   by = "sample_id")

# Remove data we no longer need
rm(filtered_expression, long_stranded_expression, expression_metadata)
```

### CN data

```{r}
# Filter focal CN data for SMARCB1 and SMARCA4 status
genes_cn_df <- cn_df %>%
  dplyr::filter(gene_symbol %in% c("SMARCB1", "SMARCA4")) %>%
  tidyr::spread(gene_symbol, status, fill = "neutral") %>%
  dplyr::rename(SMARCB1_focal_status = SMARCB1,
                SMARCA4_focal_status = SMARCA4)

# add in the samples that did not have any copy number changes for either
# of these genes
missing_cn_samples <- setdiff(unique(cn_df$sample_id), genes_cn_df$sample_id)
genes_cn_df <- subset_metadata %>%
  dplyr::filter(sample_id %in% missing_cn_samples) %>%
  dplyr::select(sample_id,
                Kids_First_Participant_ID,
                Kids_First_Biospecimen_ID) %>%
  dplyr::rename(biospecimen_id = Kids_First_Biospecimen_ID) %>%
  # bind rows fills with NAs -- if something is NA, there is no evidence for
  # a copy number alteration in that gene and we will call it neutral
  dplyr::bind_rows(genes_cn_df) %>%
  dplyr::mutate_all(function(x) tidyr::replace_na(x, "neutral"))

# Display `genes_cn_df`
genes_cn_df %>%
  head(n = 15)

# Join ATRT expression data with focal CN data
atrt_expression_cn_df <- atrt_expression_df %>%
  dplyr::left_join(dplyr::select(genes_cn_df,
                                 -biospecimen_id,
                                 -Kids_First_Participant_ID), 
                   by = "sample_id")

# Remove data we don't need 
rm(missing_cn_samples, cn_df, atrt_expression_df, genes_cn_df)
```

### GSVA data

```{r}
# Filter to only the hallmark gene sets that were named in the issue
relevant_genesets <- c("HALLMARK_MYC_TARGETS_V1",
                       "HALLMARK_MYC_TARGETS_V2",
                       "HALLMARK_NOTCH_SIGNALING")
gsva_filtered <- gsva_subset %>%
  dplyr::filter(hallmark_name %in% relevant_genesets)

# Matrix with gene set columns that can be scaled
gsva_mat <- gsva_filtered %>% 
  dplyr::select(-Kids_First_Biospecimen_ID) %>% 
  tidyr::spread(hallmark_name, gsea_score) %>%
  tibble::column_to_rownames("sample_id") %>%
  as.matrix()

# z-score scores (here they are columns)
scaled_gsva <- scale(gsva_mat, center = TRUE, scale = TRUE) %>%
  as.data.frame() %>%
  tibble::rownames_to_column("sample_id")

# Display scaled_gsva
scaled_gsva %>%
  head(n = 15)

# Join ATRT expression and focal CN data with GSVA data
atrt_expression_cn_df <- atrt_expression_cn_df %>%
  dplyr::left_join(scaled_gsva,
                   by = "sample_id")

# Remove data we no longer need
rm(gsva_filtered, gsva_mat, scaled_gsva)
```

### Tumor mutation burden data

```{r}
# Display `tmb_df`
tmb_df %>%
  head(n = 15)

# Join ATRT expression, focal CN data and transposed ssGSEA data with tumor
# mutation burden data
atrt_expression_cn_tmb_df <- atrt_expression_cn_df %>%
  dplyr::left_join(dplyr::select(tmb_df,
                                 -Tumor_Sample_Barcode,
                                 -Kids_First_Participant_ID), 
                   by = "sample_id")

# Remove data we no longer need
rm(tmb_df, atrt_expression_cn_df)
```

### GISTIC data

```{r}
gistic_df <- gistic_df %>%
  dplyr::select(-Kids_First_Biospecimen_ID) %>%
  dplyr::group_by(sample_id) %>%
  dplyr::mutate(chr_22q_loss = dplyr::case_when(`22q` == -1 ~ "Yes",
                                                TRUE ~ "No")) %>%
  dplyr::select(-`22q`)

# Display `gistic_df`
gistic_df %>%
  head(n = 15)

# Join GISTIC data with the running final data.frame
final_df <- atrt_expression_cn_tmb_df %>%
  dplyr::left_join(gistic_df, by = "sample_id") %>%
  dplyr::distinct()

# Remove data we no longer need
rm(gistic_df, atrt_expression_cn_tmb_df)
```

# Save final table of results

```{r}
# Save final data.frame
final_df <- final_df %>%
  dplyr::select(
    sample_id,
    Kids_First_Biospecimen_ID,
    Kids_First_Participant_ID,
    age_at_diagnosis_days,
    OS_months,
    germline_sex_estimate,
    primary_site,
    location_summary,
    chr_22q_loss,
    SMARCB1_focal_status,
    TYR,
    MITF,
    DCT,
    VEGFA,
    DNAH11,
    SPEF1,
    POU3F4,
    POU3F2,
    PBX1,
    SMARCA4_focal_status,
    HALLMARK_NOTCH_SIGNALING,
    MYCN,
    GLI2,
    CDK6,
    ASCL1,
    ZBTB7A,
    MYBL2,
    MXI1,
    MEIS3,
    MEIS2,
    MAX,
    INSM1,
    FOXK1,
    HALLMARK_MYC_TARGETS_V1,
    HALLMARK_MYC_TARGETS_V2,
    dplyr::everything()
  )

# Write final table to file
readr::write_tsv(final_df,
                 file.path(results_dir, "ATRT_molecular_subtypes.tsv"))

# Display `final_df`
viewDataTable(final_df) 
```

# Session Info

```{r}
sessionInfo()
```


+
---
title: "ATRT Molecular Subtyping - Data Prep"
output: 
  html_notebook:
    toc: TRUE
    toc_float: TRUE
author: Chante Bethell for ALSF CCDL
date: 2019
---

This notebook addresses the issue of molecular subtyping ATRT samples. 

# Usage

This notebook is intended to be run via the command line from the top directory
of the repository as follows:

`Rscript -e "rmarkdown::render('analyses/molecular-subtyping-ATRT/01-ATRT-molecular-subtyping-data-prep.Rmd', clean = TRUE)"`

# Set Up

```{r}
# Get `magrittr` pipe
`%>%` <- dplyr::`%>%`

# Install `DT` and `htmlwidgets` packages for displaying tables
if (!("DT" %in% installed.packages())) {
  install.packages("DT")
}
if (!("htmlwidgets" %in% installed.packages())) {
  install.packages("htmlwidgets")
}
```

## Directories and Files

```{r}
# Detect the ".git" folder -- this will in the project root directory.
# Use this as the root directory to ensure proper sourcing of functions no
# matter where this is called from
root_dir <- rprojroot::find_root(rprojroot::has_dir(".git"))

# File path to results directory
input_dir <-
  file.path(root_dir, "analyses", "molecular-subtyping-ATRT", "atrt-subset")

# File path to results directory
results_dir <-
  file.path(root_dir, "analyses", "molecular-subtyping-ATRT", "results")

if (!dir.exists(results_dir)) {
  dir.create(results_dir)
}

# Read in non-subsetted metadata
metadata <- readr::read_tsv(file.path(root_dir, "data", "pbta-histologies.tsv"))

# Read in ATRT subset metadata
subset_metadata <- metadata %>%
  dplyr::filter(short_histology == "ATRT",
                sample_type == "Tumor",
                composition == "Solid Tissue")

# Select wanted columns in metadata for merging and assign to a new object
select_metadata <- metadata %>%
  dplyr::select(sample_id,
                Kids_First_Biospecimen_ID)

# Read in ATRT subset GSVA pathway scores
gsva_subset <-
  as.data.frame(readr::read_tsv(file.path(input_dir, "atrt_gsva.tsv")))

# Read in ATRT subset z-scored RNA expression data
stranded_expression <-
  readr::read_rds(
    file.path(
      input_dir,
      "atrt_log_expression.RDS"
    )
  )

# Read in ATRT subset focal CN data
cn_df <- readr::read_tsv(
  file.path(
    input_dir,
    "atrt_focal_cn.tsv.gz"
  )
)

# Read in ATRT subset consensus mutation data
tmb_df <-
  data.table::fread(file.path(input_dir,
                              "atrt_tmb.tsv"))

# Read in ATRT subset GISTIC data
gistic_df <-
  readr::read_tsv(file.path(input_dir, "atrt_gistic_broad_values.tsv"))

```

## Custom Function

```{r}
# Custom datatable function
# Function code adapted from: https://github.com/AlexsLemonade/OpenPBTA-analysis/blob/49acc98f5ffd86853fc70f220623311e13e3ca9f/analyses/collapse-rnaseq/02-analyze-drops.Rmd#L23
viewDataTable <- function(data) {
  DT::datatable(
    data,
    rownames = FALSE,
    filter = "bottom",
    class = 'cell-border stripe',
    options = list(
      pageLength = 5,
      searchHighlight = TRUE,
      scrollX = TRUE,
      dom = 'tpi',
      initComplete = htmlwidgets::JS(
        "function(settings, json) {",
        "$(this.api().table().header()).css({'background-color':
                                            '#004467', 'color': '#fff'});",
        "}"
      )
    )
  )
}
```

# Prepare Data

## Metadata

```{r}
# Define regions of the brain (using Anatomy of the Brain figure found at
# https://www.ncbi.nlm.nih.gov/books/NBK65903/figure/CDR0000574573__205/)
supratentorial <-
  c(
    "Skull",
    "Thalamus",
    "Temporal Lobe",
    "Frontal Lobe",
    "Parietal Lobe",
    "Cerebrum",
    "Basal Ganglia",
    "Cranial Nerves NOS",
    "Basal Ganglia;Temporal Lobe",
    "Frontal Lobe;Parietal Lobe;Temporal Lobe",
    "Parietal Lobe;Temporal Lobe",
    "Frontal Lobe;Parietal Lobe"
  )

infratentorial <-
  c(
    "Cerebellum/Posterior Fossa",
    "Brain Stem- Pons;Cerebellum/Posterior Fossa",
    "Cerebellum/Posterior Fossa;Other locations NOS",
    "Brain Stem",
    "Brain Stem- Midbrain/Tectum;Ventricles",
    "Cerebellum/Posterior Fossa;Ventricles",
    "Cerebellum/Posterior Fossa;Spinal Cord- Cervical;Spinal Cord- Lumbar/Thecal Sac;Spinal Cord- Thoracic",
    "Other locations NOS;Spinal Cord- Lumbar/Thecal Sac;Spinal Cord- Thoracic;Ventricles"
  )

collapsed_metadata <- subset_metadata %>%
  dplyr::mutate(
    location_summary = dplyr::case_when(
      primary_site %in% infratentorial ~ "infratentorial",
      primary_site %in% supratentorial ~ "supratentorial",
      TRUE ~ "NA"
    ),
    # Convert `OS_days` values to months and assign new values to `OS_months`
    # column
    OS_months = OS_days / (365 / 12)
  ) %>%
  dplyr::select(
    sample_id,
    Kids_First_Biospecimen_ID,
    Kids_First_Participant_ID,
    location_summary,
    age_at_diagnosis_days,
    OS_months,
    germline_sex_estimate,
    primary_site
  ) %>%
  dplyr::group_by(
    sample_id,
    Kids_First_Participant_ID
  ) %>%
  dplyr::summarize_all(function(x) paste(sort(unique(x)), collapse = ", "))

# Display metadata subsetted for ATRT samples
collapsed_metadata %>%
  head(n = 15)
```

## Filter and join RNA expression, CN, TMB, ssGSVA and GISTIC data

### RNA expression data 

```{r}
# Define target overexpressed gene vectors
# https://github.com/AlexsLemonade/OpenPBTA-analysis/issues/244#issuecomment-576850172
tyr_genes <-
  c("TYR",
    "MITF",
    "DCT",
    "VEGFA",
    "DNAH11",
    "SPEF1",
    "MSX2",
    "STAT3",
    "PRRX1",
    "LMX1",
    "OTX2")
shh_genes <-
  c(
    "MYCN",
    "GLI2",
    "CDK6",
    "ASCL1",
    "HES5",
    "HES6",
    "DLL1",
    "DLL3",
    "LHX2",
    "TEAD1"
  )
myc_genes <-
  c(
    "MYC",
    "HOTAIR",
    "TEAD3"
  )

# Filter to only the genes of interest
filtered_expression <- stranded_expression[which(
   rownames(stranded_expression) %in% c(tyr_genes, shh_genes, myc_genes)
), ]

# scale does column centering, so we transpose first
long_stranded_expression <- scale(t(filtered_expression), 
                                  center = TRUE,
                                  scale = TRUE)

# Merge metadata with expression data
expression_metadata <- long_stranded_expression %>%
  as.data.frame() %>%
  tibble::rownames_to_column("Kids_First_Biospecimen_ID") %>% 
  dplyr::left_join(select_metadata, by = "Kids_First_Biospecimen_ID") %>%
  dplyr::select(-Kids_First_Biospecimen_ID)

# Display `expression_metadata`
expression_metadata %>%
  head(n = 15)

# Join expression data with metadata filtered for `ATRT`
atrt_expression_df <- collapsed_metadata %>%
  dplyr::left_join(expression_metadata,
                   by = "sample_id")

# Remove data we no longer need
rm(filtered_expression, long_stranded_expression, expression_metadata)
```

### CN data

```{r}
# Filter focal CN data for SMARCB1 and SMARCA4 status
genes_cn_df <- cn_df %>%
  dplyr::filter(gene_symbol %in% c("SMARCB1", "SMARCA4")) %>%
  tidyr::spread(gene_symbol, status, fill = "neutral") %>%
  dplyr::rename(SMARCB1_focal_status = SMARCB1,
                SMARCA4_focal_status = SMARCA4)

# add in the samples that did not have any copy number changes for either
# of these genes
missing_cn_samples <- setdiff(unique(cn_df$sample_id), genes_cn_df$sample_id)
genes_cn_df <- subset_metadata %>%
  dplyr::filter(sample_id %in% missing_cn_samples) %>%
  dplyr::select(sample_id,
                Kids_First_Participant_ID,
                Kids_First_Biospecimen_ID) %>%
  dplyr::rename(biospecimen_id = Kids_First_Biospecimen_ID) %>%
  # bind rows fills with NAs -- if something is NA, there is no evidence for
  # a copy number alteration in that gene and we will call it neutral
  dplyr::bind_rows(genes_cn_df) %>%
  dplyr::mutate_all(function(x) tidyr::replace_na(x, "neutral"))

# Display `genes_cn_df`
genes_cn_df %>%
  head(n = 15)

# Join ATRT expression data with focal CN data
atrt_expression_cn_df <- atrt_expression_df %>%
  dplyr::left_join(dplyr::select(genes_cn_df,
                                 -biospecimen_id,
                                 -Kids_First_Participant_ID), 
                   by = "sample_id")

# Remove data we don't need 
rm(missing_cn_samples, cn_df, atrt_expression_df, genes_cn_df)
```

### GSVA data

```{r}
# Filter to only the hallmark gene sets that were named in the issue
relevant_genesets <- c("HALLMARK_MYC_TARGETS_V1",
                       "HALLMARK_MYC_TARGETS_V2",
                       "HALLMARK_NOTCH_SIGNALING")
gsva_filtered <- gsva_subset %>%
  dplyr::filter(hallmark_name %in% relevant_genesets)

# Matrix with gene set columns that can be scaled
gsva_mat <- gsva_filtered %>% 
  dplyr::select(-Kids_First_Biospecimen_ID) %>% 
  tidyr::spread(hallmark_name, gsea_score) %>%
  tibble::column_to_rownames("sample_id") %>%
  as.matrix()

# z-score scores (here they are columns)
scaled_gsva <- scale(gsva_mat, center = TRUE, scale = TRUE) %>%
  as.data.frame() %>%
  tibble::rownames_to_column("sample_id")

# Display scaled_gsva
scaled_gsva %>%
  head(n = 15)

# Join ATRT expression and focal CN data with GSVA data
atrt_expression_cn_df <- atrt_expression_cn_df %>%
  dplyr::left_join(scaled_gsva,
                   by = "sample_id")

# Remove data we no longer need
rm(gsva_filtered, gsva_mat, scaled_gsva)
```

### Tumor mutation burden data

```{r}
# Display `tmb_df`
tmb_df %>%
  head(n = 15)

# Join ATRT expression, focal CN data and transposed ssGSEA data with tumor
# mutation burden data
atrt_expression_cn_tmb_df <- atrt_expression_cn_df %>%
  dplyr::left_join(dplyr::select(tmb_df,
                                 -Tumor_Sample_Barcode,
                                 -Kids_First_Participant_ID), 
                   by = "sample_id")

# Remove data we no longer need
rm(tmb_df, atrt_expression_cn_df)
```

### GISTIC data

```{r}
gistic_df <- gistic_df %>%
  dplyr::select(-Kids_First_Biospecimen_ID) %>%
  dplyr::group_by(sample_id) %>%
  dplyr::mutate(chr_22q_loss = dplyr::case_when(`22q` == -1 ~ "Yes",
                                                TRUE ~ "No")) %>%
  dplyr::select(-`22q`)

# Display `gistic_df`
gistic_df %>%
  head(n = 15)

# Join GISTIC data with the running final data.frame
final_df <- atrt_expression_cn_tmb_df %>%
  dplyr::left_join(gistic_df, by = "sample_id") %>%
  dplyr::distinct()

# Remove data we no longer need
rm(gistic_df, atrt_expression_cn_tmb_df)
```

# Save final table of results

```{r}
# For reordering the output, we will use the vector of genes as input but we 
# need to account for genes that are missing from the expression matrix
tyr_genes <- intersect(colnames(final_df), tyr_genes)
shh_genes <- intersect(colnames(final_df), shh_genes)
myc_genes <- intersect(colnames(final_df), myc_genes)

# Save final data.frame
final_df <- final_df %>%
  dplyr::select(
    sample_id,
    Kids_First_Biospecimen_ID,
    Kids_First_Participant_ID,
    age_at_diagnosis_days,
    OS_months,
    germline_sex_estimate,
    primary_site,
    location_summary,
    chr_22q_loss,
    SMARCB1_focal_status,
    !!! rlang::syms(tyr_genes),
    SMARCA4_focal_status,
    HALLMARK_NOTCH_SIGNALING,
    !!! rlang::syms(shh_genes),
    HALLMARK_MYC_TARGETS_V1,
    HALLMARK_MYC_TARGETS_V2,
    !!! rlang::syms(myc_genes),
    dplyr::everything()
  )

# Write final table to file
readr::write_tsv(final_df,
                 file.path(results_dir, "ATRT_molecular_subtypes.tsv"))

# Display `final_df`
viewDataTable(final_df) 
```

# Session Info

```{r}
sessionInfo()
```


diff --git a/analyses/molecular-subtyping-ATRT/README.md b/analyses/molecular-subtyping-ATRT/README.md index 5bc460eb91..7ec5bfbf91 100644 --- a/analyses/molecular-subtyping-ATRT/README.md +++ b/analyses/molecular-subtyping-ATRT/README.md @@ -1,7 +1,13 @@ # Molecular Subtyping ATRT -**Note: The files in the `atrt-subset` directory were generated via `00-subset-files-for-ATRT.R` using the the files in the [version 12 data release](https://github.com/AlexsLemonade/OpenPBTA-analysis/pull/293). -When re-running this module, you may want to regenerate the ATRT subset files using the most recent data release.** +*Note: The files in the `atrt-subset` directory were generated via `00-subset-files-for-ATRT.R` using the the files in the [version 13 data release](https://github.com/AlexsLemonade/OpenPBTA-analysis/pull/444). +When re-running this module, you may want to regenerate the ATRT subset files using the most recent data release.* + +**Module authors:** Chante Bethell ([@cbethell](https://github.com/cbethell)) and Jaclyn Taroni ([@jaclyn-taroni](https://github.com/jaclyn-taroni)) + +## Limitations + +From the analyses performed here, subtyping ATRT tumors was not clear cut and has been deferred (see: [#244 (comment)](https://github.com/AlexsLemonade/OpenPBTA-analysis/issues/244#issuecomment-579757849)). ## Usage @@ -11,7 +17,7 @@ To run all of the Rscripts in this module from the command line sequentially, us bash run-molecular-subtyping-ATRT.sh ``` -When run in this manner, `00-subset-files-for-ATRT.R` will generate subset files using whichever files are symlinked in `data` on your local machine. +**When run in this manner, `00-subset-files-for-ATRT.R` will generate subset files using whichever files are symlinked in `data` on your local machine.** `run-molecular-subtyping-ATRT.sh` is designed to be run as if it was called from this module directory even when called from outside of this directory. diff --git a/analyses/molecular-subtyping-ATRT/atrt-subset/atrt_focal_cn.tsv.gz b/analyses/molecular-subtyping-ATRT/atrt-subset/atrt_focal_cn.tsv.gz index eb0b20fcda..bed355a0db 100644 Binary files a/analyses/molecular-subtyping-ATRT/atrt-subset/atrt_focal_cn.tsv.gz and b/analyses/molecular-subtyping-ATRT/atrt-subset/atrt_focal_cn.tsv.gz differ diff --git a/analyses/molecular-subtyping-ATRT/atrt-subset/atrt_gistic_broad_values.tsv b/analyses/molecular-subtyping-ATRT/atrt-subset/atrt_gistic_broad_values.tsv index d6d09f2152..d2427bab23 100644 --- a/analyses/molecular-subtyping-ATRT/atrt-subset/atrt_gistic_broad_values.tsv +++ b/analyses/molecular-subtyping-ATRT/atrt-subset/atrt_gistic_broad_values.tsv @@ -1,30 +1,30 @@ sample_id Kids_First_Biospecimen_ID 22q -7316-2186 BS_NXZSD2KK -1 -7316-2276 BS_0FQKT8EY 0 7316-1781 BS_0EN5R1AP 0 -7316-1778 BS_WCNPE0AC -1 -7316-2141 BS_8WJR4AA3 0 -7316-3937 BS_R5G3QP11 0 -7316-386 BS_GTAJFTTR -1 -7316-3920 BS_E0S2Y0TS -1 -7316-820 BS_P7CY04E7 0 +7316-2276 BS_0FQKT8EY 0 +7316-41 BS_12ZB7R6A 0 +7316-2090 BS_19EJ85F8 0 +7316-2582 BS_1C4WCNQF 0 +7316-2187 BS_53TV75NN 0 7316-3890 BS_5WK2KXYW -1 +7316-2110 BS_6GN1FGTB 0 +7316-3680 BS_6VKKMM6M 0 +7316-376 BS_74A1TB03 0 +7316-1771 BS_859AV1DB 0 +7316-2141 BS_8WJR4AA3 0 +7316-525 BS_9KDA3HG6 0 +7316-1790 BS_A94A7EJ4 0 7316-918 BS_CKY2TTXG 0 7316-2933 BS_DE26D072 0 -7316-2269 BS_ZAT0XJE5 0 -7316-1771 BS_859AV1DB 0 +7316-3920 BS_E0S2Y0TS 0 +7316-386 BS_GTAJFTTR 0 +7316-2688 BS_JDMM2XG4 0 7316-2181 BS_NDSWS9TS -1 +7316-2186 BS_NXZSD2KK 0 +7316-820 BS_P7CY04E7 0 +7316-122 BS_QMHND3QK 0 +7316-3937 BS_R5G3QP11 0 7316-2224 BS_SCQNN2A2 0 -7316-1790 BS_A94A7EJ4 0 -7316-525 BS_9KDA3HG6 -1 -7316-479 BS_YZ0P5E8H 0 -7316-41 BS_12ZB7R6A 0 -7316-2688 BS_JDMM2XG4 0 -7316-2187 BS_53TV75NN 0 7316-1073 BS_W23ERYW3 0 -7316-122 BS_QMHND3QK 0 -7316-2090 BS_19EJ85F8 0 -7316-2110 BS_6GN1FGTB -1 -7316-2582 BS_1C4WCNQF 0 -7316-3680 BS_6VKKMM6M -1 -7316-878 BS_SWHQ8FDW 0 +7316-1778 BS_WCNPE0AC 0 +7316-479 BS_YZ0P5E8H 0 +7316-2269 BS_ZAT0XJE5 0 diff --git a/analyses/molecular-subtyping-ATRT/atrt-subset/atrt_gsva.tsv b/analyses/molecular-subtyping-ATRT/atrt-subset/atrt_gsva.tsv index 5e55aa6d24..d5dd4b4ec6 100644 --- a/analyses/molecular-subtyping-ATRT/atrt-subset/atrt_gsva.tsv +++ b/analyses/molecular-subtyping-ATRT/atrt-subset/atrt_gsva.tsv @@ -1,1501 +1,1501 @@ Kids_First_Biospecimen_ID hallmark_name gsea_score sample_id -BS_15ETQ0E4 HALLMARK_ADIPOGENESIS -0.16329031938016736 7316-41 -BS_15ETQ0E4 HALLMARK_ALLOGRAFT_REJECTION 0.5881573749192229 7316-41 -BS_15ETQ0E4 HALLMARK_ANDROGEN_RESPONSE 0.1591360065473424 7316-41 -BS_15ETQ0E4 HALLMARK_ANGIOGENESIS 0.5766231202296324 7316-41 -BS_15ETQ0E4 HALLMARK_APICAL_JUNCTION 0.252526840343039 7316-41 -BS_15ETQ0E4 HALLMARK_APICAL_SURFACE 0.15095539508728795 7316-41 -BS_15ETQ0E4 HALLMARK_APOPTOSIS 0.3451502264013942 7316-41 -BS_15ETQ0E4 HALLMARK_BILE_ACID_METABOLISM -0.2801775376963109 7316-41 -BS_15ETQ0E4 HALLMARK_CHOLESTEROL_HOMEOSTASIS -0.17647807288737352 7316-41 -BS_15ETQ0E4 HALLMARK_COAGULATION 0.3322300176048 7316-41 -BS_15ETQ0E4 HALLMARK_COMPLEMENT 0.39401235686532954 7316-41 -BS_15ETQ0E4 HALLMARK_DNA_REPAIR 0.11079215286643526 7316-41 -BS_15ETQ0E4 HALLMARK_E2F_TARGETS 0.49708574915036796 7316-41 -BS_15ETQ0E4 HALLMARK_EPITHELIAL_MESENCHYMAL_TRANSITION 0.5028440994442284 7316-41 -BS_15ETQ0E4 HALLMARK_ESTROGEN_RESPONSE_EARLY 0.050485194962787555 7316-41 -BS_15ETQ0E4 HALLMARK_ESTROGEN_RESPONSE_LATE 0.06284798626059387 7316-41 -BS_15ETQ0E4 HALLMARK_FATTY_ACID_METABOLISM -0.21212282348893485 7316-41 -BS_15ETQ0E4 HALLMARK_G2M_CHECKPOINT 0.46223190878524417 7316-41 -BS_15ETQ0E4 HALLMARK_GLYCOLYSIS 0.05172544040746177 7316-41 -BS_15ETQ0E4 HALLMARK_HEDGEHOG_SIGNALING -0.397536740971899 7316-41 -BS_15ETQ0E4 HALLMARK_HEME_METABOLISM -0.11802886192487588 7316-41 -BS_15ETQ0E4 HALLMARK_HYPOXIA 0.06662340510119685 7316-41 -BS_15ETQ0E4 HALLMARK_IL2_STAT5_SIGNALING 0.4713923024522523 7316-41 -BS_15ETQ0E4 HALLMARK_IL6_JAK_STAT3_SIGNALING 0.5250593691399963 7316-41 -BS_15ETQ0E4 HALLMARK_INFLAMMATORY_RESPONSE 0.49479694110436073 7316-41 -BS_15ETQ0E4 HALLMARK_INTERFERON_ALPHA_RESPONSE 0.4748716261209646 7316-41 -BS_15ETQ0E4 HALLMARK_INTERFERON_GAMMA_RESPONSE 0.5635336570895435 7316-41 -BS_15ETQ0E4 HALLMARK_KRAS_SIGNALING_DN -0.10999102941081332 7316-41 -BS_15ETQ0E4 HALLMARK_KRAS_SIGNALING_UP 0.30208796367712837 7316-41 -BS_15ETQ0E4 HALLMARK_MITOTIC_SPINDLE 0.14865522738610362 7316-41 -BS_15ETQ0E4 HALLMARK_MTORC1_SIGNALING 0.35992491581888986 7316-41 -BS_15ETQ0E4 HALLMARK_MYC_TARGETS_V1 0.5454170031969935 7316-41 -BS_15ETQ0E4 HALLMARK_MYC_TARGETS_V2 0.6553734783769584 7316-41 -BS_15ETQ0E4 HALLMARK_MYOGENESIS -0.030170254805372804 7316-41 -BS_15ETQ0E4 HALLMARK_NOTCH_SIGNALING -0.0781009729774155 7316-41 -BS_15ETQ0E4 HALLMARK_OXIDATIVE_PHOSPHORYLATION -0.2267083664347203 7316-41 -BS_15ETQ0E4 HALLMARK_P53_PATHWAY 0.3028596975070918 7316-41 -BS_15ETQ0E4 HALLMARK_PANCREAS_BETA_CELLS -0.26714375732831785 7316-41 -BS_15ETQ0E4 HALLMARK_PEROXISOME -0.2522010125465118 7316-41 -BS_15ETQ0E4 HALLMARK_PI3K_AKT_MTOR_SIGNALING 0.12990681580946645 7316-41 -BS_15ETQ0E4 HALLMARK_PROTEIN_SECRETION -0.1430424325434238 7316-41 -BS_15ETQ0E4 HALLMARK_REACTIVE_OXYGEN_SPECIES_PATHWAY 0.09004466127450506 7316-41 -BS_15ETQ0E4 HALLMARK_SPERMATOGENESIS -0.116933579106558 7316-41 -BS_15ETQ0E4 HALLMARK_TGF_BETA_SIGNALING 0.22953540106624742 7316-41 -BS_15ETQ0E4 HALLMARK_TNFA_SIGNALING_VIA_NFKB 0.5154168092878597 7316-41 -BS_15ETQ0E4 HALLMARK_UNFOLDED_PROTEIN_RESPONSE 0.45133727347441116 7316-41 -BS_15ETQ0E4 HALLMARK_UV_RESPONSE_DN -0.05576300640736784 7316-41 -BS_15ETQ0E4 HALLMARK_UV_RESPONSE_UP 0.22504484545764608 7316-41 -BS_15ETQ0E4 HALLMARK_WNT_BETA_CATENIN_SIGNALING 0.022115014136695504 7316-41 -BS_15ETQ0E4 HALLMARK_XENOBIOTIC_METABOLISM 0.031357122878473975 7316-41 -BS_1QNTEZPS HALLMARK_ADIPOGENESIS 0.07217371942681886 7316-525 -BS_1QNTEZPS HALLMARK_ALLOGRAFT_REJECTION 0.1359923798265551 7316-525 -BS_1QNTEZPS HALLMARK_ANDROGEN_RESPONSE 0.18452897102953197 7316-525 -BS_1QNTEZPS HALLMARK_ANGIOGENESIS 0.32665543191568214 7316-525 -BS_1QNTEZPS HALLMARK_APICAL_JUNCTION 0.1861241196410442 7316-525 -BS_1QNTEZPS HALLMARK_APICAL_SURFACE 0.3046807187553089 7316-525 -BS_1QNTEZPS HALLMARK_APOPTOSIS 0.10989098629503616 7316-525 -BS_1QNTEZPS HALLMARK_BILE_ACID_METABOLISM 0.0800481816720959 7316-525 -BS_1QNTEZPS HALLMARK_CHOLESTEROL_HOMEOSTASIS 0.13009505587246878 7316-525 -BS_1QNTEZPS HALLMARK_COAGULATION 0.025732609123102546 7316-525 -BS_1QNTEZPS HALLMARK_COMPLEMENT 0.020129929748232328 7316-525 -BS_1QNTEZPS HALLMARK_DNA_REPAIR 0.4445961645726271 7316-525 -BS_1QNTEZPS HALLMARK_E2F_TARGETS 0.6054588843215112 7316-525 -BS_1QNTEZPS HALLMARK_EPITHELIAL_MESENCHYMAL_TRANSITION 0.4007309892154218 7316-525 -BS_1QNTEZPS HALLMARK_ESTROGEN_RESPONSE_EARLY -0.06501973317886783 7316-525 -BS_1QNTEZPS HALLMARK_ESTROGEN_RESPONSE_LATE 0.04939680928481652 7316-525 -BS_1QNTEZPS HALLMARK_FATTY_ACID_METABOLISM 0.1729041543425594 7316-525 -BS_1QNTEZPS HALLMARK_G2M_CHECKPOINT 0.5160268781640249 7316-525 -BS_1QNTEZPS HALLMARK_GLYCOLYSIS 0.26728047202437794 7316-525 -BS_1QNTEZPS HALLMARK_HEDGEHOG_SIGNALING -0.5058675157182084 7316-525 -BS_1QNTEZPS HALLMARK_HEME_METABOLISM -0.020751060271246846 7316-525 -BS_1QNTEZPS HALLMARK_HYPOXIA 0.014924894176850362 7316-525 -BS_1QNTEZPS HALLMARK_IL2_STAT5_SIGNALING 0.3036863913060651 7316-525 -BS_1QNTEZPS HALLMARK_IL6_JAK_STAT3_SIGNALING 0.0701603173128523 7316-525 -BS_1QNTEZPS HALLMARK_INFLAMMATORY_RESPONSE 0.13392910244226006 7316-525 -BS_1QNTEZPS HALLMARK_INTERFERON_ALPHA_RESPONSE -0.21464345977666904 7316-525 -BS_1QNTEZPS HALLMARK_INTERFERON_GAMMA_RESPONSE -0.04486049232653261 7316-525 -BS_1QNTEZPS HALLMARK_KRAS_SIGNALING_DN -0.16909802729582823 7316-525 -BS_1QNTEZPS HALLMARK_KRAS_SIGNALING_UP 0.062320884473667376 7316-525 -BS_1QNTEZPS HALLMARK_MITOTIC_SPINDLE 0.23269018694735313 7316-525 -BS_1QNTEZPS HALLMARK_MTORC1_SIGNALING 0.3808439739781547 7316-525 -BS_1QNTEZPS HALLMARK_MYC_TARGETS_V1 0.6343334517087128 7316-525 -BS_1QNTEZPS HALLMARK_MYC_TARGETS_V2 0.45820479783392576 7316-525 -BS_1QNTEZPS HALLMARK_MYOGENESIS -0.24385866376551724 7316-525 -BS_1QNTEZPS HALLMARK_NOTCH_SIGNALING 0.011515081242791825 7316-525 -BS_1QNTEZPS HALLMARK_OXIDATIVE_PHOSPHORYLATION 0.48355283129906645 7316-525 -BS_1QNTEZPS HALLMARK_P53_PATHWAY 0.14094062483049324 7316-525 -BS_1QNTEZPS HALLMARK_PANCREAS_BETA_CELLS -0.3507758237331794 7316-525 -BS_1QNTEZPS HALLMARK_PEROXISOME 0.24617211104527814 7316-525 -BS_1QNTEZPS HALLMARK_PI3K_AKT_MTOR_SIGNALING 0.27168502247403364 7316-525 -BS_1QNTEZPS HALLMARK_PROTEIN_SECRETION 0.19783733051740454 7316-525 -BS_1QNTEZPS HALLMARK_REACTIVE_OXYGEN_SPECIES_PATHWAY 0.28916995490546116 7316-525 -BS_1QNTEZPS HALLMARK_SPERMATOGENESIS 0.24559797115636772 7316-525 -BS_1QNTEZPS HALLMARK_TGF_BETA_SIGNALING 0.38358679074876395 7316-525 -BS_1QNTEZPS HALLMARK_TNFA_SIGNALING_VIA_NFKB -0.018351682882004033 7316-525 -BS_1QNTEZPS HALLMARK_UNFOLDED_PROTEIN_RESPONSE 0.33125573941170394 7316-525 -BS_1QNTEZPS HALLMARK_UV_RESPONSE_DN 0.10038637207027815 7316-525 -BS_1QNTEZPS HALLMARK_UV_RESPONSE_UP 0.2822518951636026 7316-525 -BS_1QNTEZPS HALLMARK_WNT_BETA_CATENIN_SIGNALING 0.2757999800532412 7316-525 -BS_1QNTEZPS HALLMARK_XENOBIOTIC_METABOLISM 0.10582907397835772 7316-525 -BS_31TF0P1N HALLMARK_ADIPOGENESIS -0.053993555529142284 7316-918 -BS_31TF0P1N HALLMARK_ALLOGRAFT_REJECTION 0.31288807069475266 7316-918 -BS_31TF0P1N HALLMARK_ANDROGEN_RESPONSE 0.26625206751573005 7316-918 -BS_31TF0P1N HALLMARK_ANGIOGENESIS 0.4137832201353816 7316-918 -BS_31TF0P1N HALLMARK_APICAL_JUNCTION 0.21714467468759444 7316-918 -BS_31TF0P1N HALLMARK_APICAL_SURFACE 0.10282821588718685 7316-918 -BS_31TF0P1N HALLMARK_APOPTOSIS 0.33221988762065746 7316-918 -BS_31TF0P1N HALLMARK_BILE_ACID_METABOLISM -0.27759553225167166 7316-918 -BS_31TF0P1N HALLMARK_CHOLESTEROL_HOMEOSTASIS 0.08988556005895276 7316-918 -BS_31TF0P1N HALLMARK_COAGULATION 0.29151453176367464 7316-918 -BS_31TF0P1N HALLMARK_COMPLEMENT 0.17633051142801054 7316-918 -BS_31TF0P1N HALLMARK_DNA_REPAIR -0.10863943389463548 7316-918 -BS_31TF0P1N HALLMARK_E2F_TARGETS 0.3613744965723903 7316-918 -BS_31TF0P1N HALLMARK_EPITHELIAL_MESENCHYMAL_TRANSITION 0.5672672313133247 7316-918 -BS_31TF0P1N HALLMARK_ESTROGEN_RESPONSE_EARLY 0.10906236710637887 7316-918 -BS_31TF0P1N HALLMARK_ESTROGEN_RESPONSE_LATE 0.21341871628372575 7316-918 -BS_31TF0P1N HALLMARK_FATTY_ACID_METABOLISM -0.03916769445617596 7316-918 -BS_31TF0P1N HALLMARK_G2M_CHECKPOINT 0.27834776430598196 7316-918 -BS_31TF0P1N HALLMARK_GLYCOLYSIS 0.3876226571952553 7316-918 -BS_31TF0P1N HALLMARK_HEDGEHOG_SIGNALING -0.3243191708125326 7316-918 -BS_31TF0P1N HALLMARK_HEME_METABOLISM -0.040910457031465314 7316-918 -BS_31TF0P1N HALLMARK_HYPOXIA 0.41006103103809977 7316-918 -BS_31TF0P1N HALLMARK_IL2_STAT5_SIGNALING 0.2970856741265783 7316-918 -BS_31TF0P1N HALLMARK_IL6_JAK_STAT3_SIGNALING 0.4185568541104927 7316-918 -BS_31TF0P1N HALLMARK_INFLAMMATORY_RESPONSE 0.3514106542121526 7316-918 -BS_31TF0P1N HALLMARK_INTERFERON_ALPHA_RESPONSE 0.1919561321663864 7316-918 -BS_31TF0P1N HALLMARK_INTERFERON_GAMMA_RESPONSE 0.21989693490784648 7316-918 -BS_31TF0P1N HALLMARK_KRAS_SIGNALING_DN -0.22042732501811207 7316-918 -BS_31TF0P1N HALLMARK_KRAS_SIGNALING_UP 0.1049978820801214 7316-918 -BS_31TF0P1N HALLMARK_MITOTIC_SPINDLE 0.02510393289585064 7316-918 -BS_31TF0P1N HALLMARK_MTORC1_SIGNALING 0.39929037442545934 7316-918 -BS_31TF0P1N HALLMARK_MYC_TARGETS_V1 0.5534575836027814 7316-918 -BS_31TF0P1N HALLMARK_MYC_TARGETS_V2 0.6730328665234055 7316-918 -BS_31TF0P1N HALLMARK_MYOGENESIS 0.06665568507053762 7316-918 -BS_31TF0P1N HALLMARK_NOTCH_SIGNALING -0.12197702973975028 7316-918 -BS_31TF0P1N HALLMARK_OXIDATIVE_PHOSPHORYLATION 0.024562744594090608 7316-918 -BS_31TF0P1N HALLMARK_P53_PATHWAY 0.2561788499738886 7316-918 -BS_31TF0P1N HALLMARK_PANCREAS_BETA_CELLS -0.18845451743744243 7316-918 -BS_31TF0P1N HALLMARK_PEROXISOME -0.22526204771054945 7316-918 -BS_31TF0P1N HALLMARK_PI3K_AKT_MTOR_SIGNALING 0.009435041120839982 7316-918 -BS_31TF0P1N HALLMARK_PROTEIN_SECRETION 0.029616290765189568 7316-918 -BS_31TF0P1N HALLMARK_REACTIVE_OXYGEN_SPECIES_PATHWAY 0.29090724004256846 7316-918 -BS_31TF0P1N HALLMARK_SPERMATOGENESIS -0.1589965498290707 7316-918 -BS_31TF0P1N HALLMARK_TGF_BETA_SIGNALING 0.22454304218495363 7316-918 -BS_31TF0P1N HALLMARK_TNFA_SIGNALING_VIA_NFKB 0.49401420984200073 7316-918 -BS_31TF0P1N HALLMARK_UNFOLDED_PROTEIN_RESPONSE 0.321931735263403 7316-918 -BS_31TF0P1N HALLMARK_UV_RESPONSE_DN -0.03047269799905694 7316-918 -BS_31TF0P1N HALLMARK_UV_RESPONSE_UP 0.1395560164769911 7316-918 -BS_31TF0P1N HALLMARK_WNT_BETA_CATENIN_SIGNALING -0.21122902211035596 7316-918 -BS_31TF0P1N HALLMARK_XENOBIOTIC_METABOLISM 0.024221947714847508 7316-918 -BS_4E1G7E3G HALLMARK_ADIPOGENESIS -0.5677706782693178 7316-2110 -BS_4E1G7E3G HALLMARK_ALLOGRAFT_REJECTION -0.5427275262658943 7316-2110 -BS_4E1G7E3G HALLMARK_ANDROGEN_RESPONSE -0.42879914676381276 7316-2110 -BS_4E1G7E3G HALLMARK_ANGIOGENESIS -0.1806548616295217 7316-2110 -BS_4E1G7E3G HALLMARK_APICAL_JUNCTION -0.1512309235230062 7316-2110 -BS_4E1G7E3G HALLMARK_APICAL_SURFACE -0.10561547916175998 7316-2110 -BS_4E1G7E3G HALLMARK_APOPTOSIS -0.41821144566716867 7316-2110 -BS_4E1G7E3G HALLMARK_BILE_ACID_METABOLISM -0.3215594259874012 7316-2110 -BS_4E1G7E3G HALLMARK_CHOLESTEROL_HOMEOSTASIS -0.37545218744040776 7316-2110 -BS_4E1G7E3G HALLMARK_COAGULATION -0.5042958684654393 7316-2110 -BS_4E1G7E3G HALLMARK_COMPLEMENT -0.5063226337666943 7316-2110 -BS_4E1G7E3G HALLMARK_DNA_REPAIR -0.08037409350700139 7316-2110 -BS_4E1G7E3G HALLMARK_E2F_TARGETS 0.3613172690967539 7316-2110 -BS_4E1G7E3G HALLMARK_EPITHELIAL_MESENCHYMAL_TRANSITION -0.3128763439571734 7316-2110 -BS_4E1G7E3G HALLMARK_ESTROGEN_RESPONSE_EARLY -0.33898715502639165 7316-2110 -BS_4E1G7E3G HALLMARK_ESTROGEN_RESPONSE_LATE -0.3483627757743098 7316-2110 -BS_4E1G7E3G 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HALLMARK_COAGULATION -0.3330767372377307 7316-1778 -BS_B1HVNV0T HALLMARK_COMPLEMENT -0.3165325065106864 7316-1778 -BS_B1HVNV0T HALLMARK_DNA_REPAIR -0.4799016718424967 7316-1778 -BS_B1HVNV0T HALLMARK_E2F_TARGETS -0.6117750678414574 7316-1778 -BS_B1HVNV0T HALLMARK_EPITHELIAL_MESENCHYMAL_TRANSITION -0.5409521110433658 7316-1778 -BS_B1HVNV0T HALLMARK_ESTROGEN_RESPONSE_EARLY -0.1280097526422003 7316-1778 -BS_B1HVNV0T HALLMARK_ESTROGEN_RESPONSE_LATE -0.14274694100740098 7316-1778 -BS_B1HVNV0T HALLMARK_FATTY_ACID_METABOLISM -0.15631694341994296 7316-1778 -BS_B1HVNV0T HALLMARK_G2M_CHECKPOINT -0.6034243261887148 7316-1778 -BS_B1HVNV0T HALLMARK_GLYCOLYSIS -0.25253078801596673 7316-1778 -BS_B1HVNV0T HALLMARK_HEDGEHOG_SIGNALING 0.2571098298806862 7316-1778 -BS_B1HVNV0T HALLMARK_HEME_METABOLISM -0.0922831178715593 7316-1778 -BS_B1HVNV0T HALLMARK_HYPOXIA -0.2982705210661728 7316-1778 -BS_B1HVNV0T HALLMARK_IL2_STAT5_SIGNALING -0.33492986963924176 7316-1778 -BS_B1HVNV0T HALLMARK_IL6_JAK_STAT3_SIGNALING -0.33908713649595157 7316-1778 -BS_B1HVNV0T HALLMARK_INFLAMMATORY_RESPONSE -0.28095645103911765 7316-1778 -BS_B1HVNV0T HALLMARK_INTERFERON_ALPHA_RESPONSE 0.5637305590950489 7316-1778 -BS_B1HVNV0T HALLMARK_INTERFERON_GAMMA_RESPONSE 0.2020374418948505 7316-1778 -BS_B1HVNV0T HALLMARK_KRAS_SIGNALING_DN 0.21145833533793235 7316-1778 -BS_B1HVNV0T HALLMARK_KRAS_SIGNALING_UP -0.24701227855931984 7316-1778 -BS_B1HVNV0T HALLMARK_MITOTIC_SPINDLE -0.4258536483969773 7316-1778 -BS_B1HVNV0T HALLMARK_MTORC1_SIGNALING -0.23762985563754022 7316-1778 -BS_B1HVNV0T HALLMARK_MYC_TARGETS_V1 -0.5476964856239054 7316-1778 -BS_B1HVNV0T HALLMARK_MYC_TARGETS_V2 -0.47190377670450906 7316-1778 -BS_B1HVNV0T HALLMARK_MYOGENESIS -0.18040618572865244 7316-1778 -BS_B1HVNV0T HALLMARK_NOTCH_SIGNALING -0.2064973520269676 7316-1778 -BS_B1HVNV0T HALLMARK_OXIDATIVE_PHOSPHORYLATION 0.23427670113334353 7316-1778 -BS_B1HVNV0T HALLMARK_P53_PATHWAY -0.37814656927056284 7316-1778 -BS_B1HVNV0T HALLMARK_PANCREAS_BETA_CELLS 0.340777139418751 7316-1778 -BS_B1HVNV0T HALLMARK_PEROXISOME -0.16408516737174608 7316-1778 -BS_B1HVNV0T HALLMARK_PI3K_AKT_MTOR_SIGNALING -0.22997732598714213 7316-1778 -BS_B1HVNV0T HALLMARK_PROTEIN_SECRETION -0.13380895081681624 7316-1778 -BS_B1HVNV0T HALLMARK_REACTIVE_OXYGEN_SPECIES_PATHWAY -0.22316237732210326 7316-1778 -BS_B1HVNV0T HALLMARK_SPERMATOGENESIS 0.14709812942014416 7316-1778 -BS_B1HVNV0T HALLMARK_TGF_BETA_SIGNALING -0.46201953915531024 7316-1778 -BS_B1HVNV0T HALLMARK_TNFA_SIGNALING_VIA_NFKB -0.3435531558793621 7316-1778 -BS_B1HVNV0T HALLMARK_UNFOLDED_PROTEIN_RESPONSE -0.39437466943086286 7316-1778 -BS_B1HVNV0T HALLMARK_UV_RESPONSE_DN -0.1847524370554033 7316-1778 -BS_B1HVNV0T HALLMARK_UV_RESPONSE_UP -0.05482991166223822 7316-1778 -BS_B1HVNV0T HALLMARK_WNT_BETA_CATENIN_SIGNALING -0.3247835424175403 7316-1778 -BS_B1HVNV0T HALLMARK_XENOBIOTIC_METABOLISM -0.20981940810160374 7316-1778 -BS_DHA5FMVW HALLMARK_ADIPOGENESIS -0.24756059635978273 7316-122 -BS_DHA5FMVW HALLMARK_ALLOGRAFT_REJECTION 0.36050685785269626 7316-122 -BS_DHA5FMVW HALLMARK_ANDROGEN_RESPONSE -0.09796872833402454 7316-122 -BS_DHA5FMVW HALLMARK_ANGIOGENESIS -0.17783869063372887 7316-122 -BS_DHA5FMVW HALLMARK_APICAL_JUNCTION -0.016876343079411577 7316-122 -BS_DHA5FMVW HALLMARK_APICAL_SURFACE -0.08660358331345006 7316-122 -BS_DHA5FMVW HALLMARK_APOPTOSIS 0.013891736599600829 7316-122 -BS_DHA5FMVW HALLMARK_BILE_ACID_METABOLISM -0.28378794780087824 7316-122 -BS_DHA5FMVW HALLMARK_CHOLESTEROL_HOMEOSTASIS -0.20331596413905845 7316-122 -BS_DHA5FMVW HALLMARK_COAGULATION -0.07061835653170817 7316-122 -BS_DHA5FMVW HALLMARK_COMPLEMENT 0.018267915711685928 7316-122 -BS_DHA5FMVW HALLMARK_DNA_REPAIR 0.38893957671170565 7316-122 -BS_DHA5FMVW HALLMARK_E2F_TARGETS 0.5621150994553985 7316-122 -BS_DHA5FMVW HALLMARK_EPITHELIAL_MESENCHYMAL_TRANSITION 0.060434985353791465 7316-122 -BS_DHA5FMVW HALLMARK_ESTROGEN_RESPONSE_EARLY -0.2753008670694173 7316-122 -BS_DHA5FMVW HALLMARK_ESTROGEN_RESPONSE_LATE -0.2427383786881358 7316-122 -BS_DHA5FMVW HALLMARK_FATTY_ACID_METABOLISM -0.08534526172934925 7316-122 -BS_DHA5FMVW HALLMARK_G2M_CHECKPOINT 0.4651816149680115 7316-122 -BS_DHA5FMVW HALLMARK_GLYCOLYSIS -0.0318247171935061 7316-122 -BS_DHA5FMVW HALLMARK_HEDGEHOG_SIGNALING -0.39093365472348884 7316-122 -BS_DHA5FMVW HALLMARK_HEME_METABOLISM -0.18877045915720625 7316-122 -BS_DHA5FMVW HALLMARK_HYPOXIA -0.17256890467914499 7316-122 -BS_DHA5FMVW HALLMARK_IL2_STAT5_SIGNALING 0.1019420978305392 7316-122 -BS_DHA5FMVW HALLMARK_IL6_JAK_STAT3_SIGNALING 0.0688057568548884 7316-122 -BS_DHA5FMVW HALLMARK_INFLAMMATORY_RESPONSE -0.08761759598615534 7316-122 -BS_DHA5FMVW HALLMARK_INTERFERON_ALPHA_RESPONSE 0.3227253448517999 7316-122 -BS_DHA5FMVW HALLMARK_INTERFERON_GAMMA_RESPONSE 0.36920590175830115 7316-122 -BS_DHA5FMVW HALLMARK_KRAS_SIGNALING_DN -0.26624313021128976 7316-122 -BS_DHA5FMVW HALLMARK_KRAS_SIGNALING_UP -0.1684754247273812 7316-122 -BS_DHA5FMVW HALLMARK_MITOTIC_SPINDLE 0.08706435400510804 7316-122 -BS_DHA5FMVW HALLMARK_MTORC1_SIGNALING 0.20788904381384776 7316-122 -BS_DHA5FMVW HALLMARK_MYC_TARGETS_V1 0.5851225453108587 7316-122 -BS_DHA5FMVW HALLMARK_MYC_TARGETS_V2 0.6395397965131419 7316-122 -BS_DHA5FMVW HALLMARK_MYOGENESIS -0.2848521777254764 7316-122 -BS_DHA5FMVW HALLMARK_NOTCH_SIGNALING -0.3736401087350096 7316-122 -BS_DHA5FMVW HALLMARK_OXIDATIVE_PHOSPHORYLATION 0.22767173900912713 7316-122 -BS_DHA5FMVW HALLMARK_P53_PATHWAY 0.05669220229838734 7316-122 -BS_DHA5FMVW HALLMARK_PANCREAS_BETA_CELLS -0.40684243941058407 7316-122 -BS_DHA5FMVW HALLMARK_PEROXISOME -0.14649221974489274 7316-122 -BS_DHA5FMVW HALLMARK_PI3K_AKT_MTOR_SIGNALING 0.0732879303571411 7316-122 -BS_DHA5FMVW HALLMARK_PROTEIN_SECRETION 0.06157178325735771 7316-122 -BS_DHA5FMVW HALLMARK_REACTIVE_OXYGEN_SPECIES_PATHWAY -0.0391347972266492 7316-122 -BS_DHA5FMVW HALLMARK_SPERMATOGENESIS -0.02489045305319179 7316-122 -BS_DHA5FMVW HALLMARK_TGF_BETA_SIGNALING 0.1356660183143917 7316-122 -BS_DHA5FMVW HALLMARK_TNFA_SIGNALING_VIA_NFKB -0.046532937511733874 7316-122 -BS_DHA5FMVW HALLMARK_UNFOLDED_PROTEIN_RESPONSE 0.4070272729507708 7316-122 -BS_DHA5FMVW HALLMARK_UV_RESPONSE_DN -0.14465744933009325 7316-122 -BS_DHA5FMVW HALLMARK_UV_RESPONSE_UP 0.01142956894302466 7316-122 -BS_DHA5FMVW HALLMARK_WNT_BETA_CATENIN_SIGNALING -0.2517331160262326 7316-122 -BS_DHA5FMVW HALLMARK_XENOBIOTIC_METABOLISM -0.06991280763058601 7316-122 -BS_GAGRGSSX HALLMARK_ADIPOGENESIS -0.08604333825780547 7316-1137 -BS_GAGRGSSX HALLMARK_ALLOGRAFT_REJECTION 0.5266816316470219 7316-1137 -BS_GAGRGSSX HALLMARK_ANDROGEN_RESPONSE -0.0157554162347624 7316-1137 -BS_GAGRGSSX HALLMARK_ANGIOGENESIS 0.16446236559621083 7316-1137 -BS_GAGRGSSX HALLMARK_APICAL_JUNCTION 0.18603348800704406 7316-1137 -BS_GAGRGSSX HALLMARK_APICAL_SURFACE 0.030493129962742005 7316-1137 -BS_GAGRGSSX HALLMARK_APOPTOSIS 0.16885747484185049 7316-1137 -BS_GAGRGSSX HALLMARK_BILE_ACID_METABOLISM -0.2390970763344748 7316-1137 -BS_GAGRGSSX HALLMARK_CHOLESTEROL_HOMEOSTASIS -0.08640813166100195 7316-1137 -BS_GAGRGSSX HALLMARK_COAGULATION 0.14174077125602713 7316-1137 -BS_GAGRGSSX HALLMARK_COMPLEMENT 0.31858776403343014 7316-1137 -BS_GAGRGSSX HALLMARK_DNA_REPAIR 0.27705957111675594 7316-1137 -BS_GAGRGSSX HALLMARK_E2F_TARGETS 0.5056225319282925 7316-1137 -BS_GAGRGSSX HALLMARK_EPITHELIAL_MESENCHYMAL_TRANSITION 0.2777667515314065 7316-1137 -BS_GAGRGSSX HALLMARK_ESTROGEN_RESPONSE_EARLY -0.16441770546424647 7316-1137 -BS_GAGRGSSX HALLMARK_ESTROGEN_RESPONSE_LATE -0.05328282144396457 7316-1137 -BS_GAGRGSSX HALLMARK_FATTY_ACID_METABOLISM -0.020837050116651767 7316-1137 -BS_GAGRGSSX HALLMARK_G2M_CHECKPOINT 0.46687730494343327 7316-1137 -BS_GAGRGSSX HALLMARK_GLYCOLYSIS 0.14110337322876823 7316-1137 -BS_GAGRGSSX HALLMARK_HEDGEHOG_SIGNALING -0.4502149106968085 7316-1137 -BS_GAGRGSSX HALLMARK_HEME_METABOLISM -0.17184565558568085 7316-1137 -BS_GAGRGSSX HALLMARK_HYPOXIA 0.05653772227146445 7316-1137 -BS_GAGRGSSX HALLMARK_IL2_STAT5_SIGNALING 0.24504231523426778 7316-1137 -BS_GAGRGSSX HALLMARK_IL6_JAK_STAT3_SIGNALING 0.459045049665347 7316-1137 -BS_GAGRGSSX HALLMARK_INFLAMMATORY_RESPONSE 0.4395841463196473 7316-1137 -BS_GAGRGSSX HALLMARK_INTERFERON_ALPHA_RESPONSE 0.716555816589368 7316-1137 -BS_GAGRGSSX HALLMARK_INTERFERON_GAMMA_RESPONSE 0.6477872347081443 7316-1137 -BS_GAGRGSSX HALLMARK_KRAS_SIGNALING_DN -0.13589911530703735 7316-1137 -BS_GAGRGSSX HALLMARK_KRAS_SIGNALING_UP 0.061047400353933134 7316-1137 -BS_GAGRGSSX HALLMARK_MITOTIC_SPINDLE 0.10166731357640557 7316-1137 -BS_GAGRGSSX HALLMARK_MTORC1_SIGNALING 0.27825637974978307 7316-1137 -BS_GAGRGSSX HALLMARK_MYC_TARGETS_V1 0.456638886279918 7316-1137 -BS_GAGRGSSX HALLMARK_MYC_TARGETS_V2 0.5980503260259894 7316-1137 -BS_GAGRGSSX HALLMARK_MYOGENESIS -0.11712003624753103 7316-1137 -BS_GAGRGSSX HALLMARK_NOTCH_SIGNALING -0.273855390754157 7316-1137 -BS_GAGRGSSX HALLMARK_OXIDATIVE_PHOSPHORYLATION 0.027211345641313195 7316-1137 -BS_GAGRGSSX HALLMARK_P53_PATHWAY 0.1612416658964837 7316-1137 -BS_GAGRGSSX HALLMARK_PANCREAS_BETA_CELLS -0.4002340782973915 7316-1137 -BS_GAGRGSSX HALLMARK_PEROXISOME -0.07065496775391564 7316-1137 -BS_GAGRGSSX HALLMARK_PI3K_AKT_MTOR_SIGNALING 0.20188330517804357 7316-1137 -BS_GAGRGSSX HALLMARK_PROTEIN_SECRETION -0.05868495156936904 7316-1137 -BS_GAGRGSSX HALLMARK_REACTIVE_OXYGEN_SPECIES_PATHWAY 0.16214755452601123 7316-1137 -BS_GAGRGSSX HALLMARK_SPERMATOGENESIS -0.22512685705381752 7316-1137 -BS_GAGRGSSX HALLMARK_TGF_BETA_SIGNALING 0.17741583742397343 7316-1137 -BS_GAGRGSSX HALLMARK_TNFA_SIGNALING_VIA_NFKB 0.26525012401543674 7316-1137 -BS_GAGRGSSX HALLMARK_UNFOLDED_PROTEIN_RESPONSE 0.3599437932217303 7316-1137 -BS_GAGRGSSX HALLMARK_UV_RESPONSE_DN -0.22097601875481063 7316-1137 -BS_GAGRGSSX HALLMARK_UV_RESPONSE_UP 0.008212674082411525 7316-1137 -BS_GAGRGSSX HALLMARK_WNT_BETA_CATENIN_SIGNALING -0.06978652886099176 7316-1137 -BS_GAGRGSSX HALLMARK_XENOBIOTIC_METABOLISM 0.04712666866318052 7316-1137 -BS_GJNCYABP HALLMARK_ADIPOGENESIS 0.1205265522183837 7316-2582 -BS_GJNCYABP HALLMARK_ALLOGRAFT_REJECTION 0.6438906965413302 7316-2582 -BS_GJNCYABP HALLMARK_ANDROGEN_RESPONSE 0.31261176488159315 7316-2582 -BS_GJNCYABP HALLMARK_ANGIOGENESIS -0.15178132033722005 7316-2582 -BS_GJNCYABP HALLMARK_APICAL_JUNCTION -0.07569640795335411 7316-2582 -BS_GJNCYABP HALLMARK_APICAL_SURFACE 0.08505558331432694 7316-2582 -BS_GJNCYABP HALLMARK_APOPTOSIS 0.34848370108267607 7316-2582 -BS_GJNCYABP HALLMARK_BILE_ACID_METABOLISM 0.12251279514412086 7316-2582 -BS_GJNCYABP HALLMARK_CHOLESTEROL_HOMEOSTASIS 0.23988572993599772 7316-2582 -BS_GJNCYABP HALLMARK_COAGULATION 0.16795929823152894 7316-2582 -BS_GJNCYABP HALLMARK_COMPLEMENT 0.3922715554894704 7316-2582 -BS_GJNCYABP HALLMARK_DNA_REPAIR 0.3346745765305864 7316-2582 -BS_GJNCYABP HALLMARK_E2F_TARGETS 0.46756387628620133 7316-2582 -BS_GJNCYABP HALLMARK_EPITHELIAL_MESENCHYMAL_TRANSITION 0.003432324637161699 7316-2582 -BS_GJNCYABP HALLMARK_ESTROGEN_RESPONSE_EARLY 0.049591908562112985 7316-2582 -BS_GJNCYABP HALLMARK_ESTROGEN_RESPONSE_LATE 0.15095558724925282 7316-2582 -BS_GJNCYABP HALLMARK_FATTY_ACID_METABOLISM 0.18998940506383205 7316-2582 -BS_GJNCYABP HALLMARK_G2M_CHECKPOINT 0.3560958960216045 7316-2582 -BS_GJNCYABP HALLMARK_GLYCOLYSIS 0.20460434534823257 7316-2582 -BS_GJNCYABP HALLMARK_HEDGEHOG_SIGNALING -0.2359277668564344 7316-2582 -BS_GJNCYABP HALLMARK_HEME_METABOLISM 0.017806722150974785 7316-2582 -BS_GJNCYABP HALLMARK_HYPOXIA 0.20659763852747168 7316-2582 -BS_GJNCYABP HALLMARK_IL2_STAT5_SIGNALING 0.4458543608608637 7316-2582 -BS_GJNCYABP HALLMARK_IL6_JAK_STAT3_SIGNALING 0.5515617677063693 7316-2582 -BS_GJNCYABP HALLMARK_INFLAMMATORY_RESPONSE 0.5353966464928835 7316-2582 -BS_GJNCYABP HALLMARK_INTERFERON_ALPHA_RESPONSE 0.7179378772832118 7316-2582 -BS_GJNCYABP HALLMARK_INTERFERON_GAMMA_RESPONSE 0.691636977058688 7316-2582 -BS_GJNCYABP HALLMARK_KRAS_SIGNALING_DN -0.024406698762170942 7316-2582 -BS_GJNCYABP 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HALLMARK_TGF_BETA_SIGNALING 0.342380545040697 7316-2187 +BS_850BAHH9 HALLMARK_TNFA_SIGNALING_VIA_NFKB 0.5804783287870411 7316-2187 +BS_850BAHH9 HALLMARK_UNFOLDED_PROTEIN_RESPONSE 0.5128168006803075 7316-2187 +BS_850BAHH9 HALLMARK_UV_RESPONSE_DN 0.2753266710245609 7316-2187 +BS_850BAHH9 HALLMARK_UV_RESPONSE_UP 0.2993399729971796 7316-2187 +BS_850BAHH9 HALLMARK_WNT_BETA_CATENIN_SIGNALING 0.12433616867844485 7316-2187 +BS_850BAHH9 HALLMARK_XENOBIOTIC_METABOLISM 0.2560761993996121 7316-2187 +BS_90B22NGP HALLMARK_ADIPOGENESIS -0.48748660893735213 7316-479 +BS_90B22NGP HALLMARK_ALLOGRAFT_REJECTION -0.6005436876078307 7316-479 +BS_90B22NGP HALLMARK_ANDROGEN_RESPONSE -0.3965123790716918 7316-479 +BS_90B22NGP HALLMARK_ANGIOGENESIS -0.5463436413240434 7316-479 +BS_90B22NGP HALLMARK_APICAL_JUNCTION -0.15434315841062896 7316-479 +BS_90B22NGP HALLMARK_APICAL_SURFACE -0.15851875660702083 7316-479 +BS_90B22NGP HALLMARK_APOPTOSIS -0.5399018679865525 7316-479 +BS_90B22NGP HALLMARK_BILE_ACID_METABOLISM 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HALLMARK_IL2_STAT5_SIGNALING -0.47507180805204197 7316-479 +BS_90B22NGP HALLMARK_IL6_JAK_STAT3_SIGNALING -0.5615205883531456 7316-479 +BS_90B22NGP HALLMARK_INFLAMMATORY_RESPONSE -0.49138966779104465 7316-479 +BS_90B22NGP HALLMARK_INTERFERON_ALPHA_RESPONSE -0.6734173924177895 7316-479 +BS_90B22NGP HALLMARK_INTERFERON_GAMMA_RESPONSE -0.6190449827245359 7316-479 +BS_90B22NGP HALLMARK_KRAS_SIGNALING_DN 0.10644374268848662 7316-479 +BS_90B22NGP HALLMARK_KRAS_SIGNALING_UP -0.4059107077666967 7316-479 +BS_90B22NGP HALLMARK_MITOTIC_SPINDLE -0.18877929960089188 7316-479 +BS_90B22NGP HALLMARK_MTORC1_SIGNALING -0.5841205036840661 7316-479 +BS_90B22NGP HALLMARK_MYC_TARGETS_V1 -0.6814217652049123 7316-479 +BS_90B22NGP HALLMARK_MYC_TARGETS_V2 -0.5315175908296857 7316-479 +BS_90B22NGP HALLMARK_MYOGENESIS -0.13943192802245313 7316-479 +BS_90B22NGP HALLMARK_NOTCH_SIGNALING -0.4824213497297565 7316-479 +BS_90B22NGP HALLMARK_OXIDATIVE_PHOSPHORYLATION -0.5921644412758544 7316-479 +BS_90B22NGP 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HALLMARK_MYC_TARGETS_V1 0.564817434997771 7316-878 +BS_J483EMFP HALLMARK_MYC_TARGETS_V2 0.7160283130641738 7316-878 +BS_J483EMFP HALLMARK_MYOGENESIS -0.24474259193655723 7316-878 +BS_J483EMFP HALLMARK_NOTCH_SIGNALING 0.04737121915554149 7316-878 +BS_J483EMFP HALLMARK_OXIDATIVE_PHOSPHORYLATION 0.3919111052760541 7316-878 +BS_J483EMFP HALLMARK_P53_PATHWAY 0.10597840867276645 7316-878 +BS_J483EMFP HALLMARK_PANCREAS_BETA_CELLS 0.35533054080697707 7316-878 +BS_J483EMFP HALLMARK_PEROXISOME 0.058660362218384415 7316-878 +BS_J483EMFP HALLMARK_PI3K_AKT_MTOR_SIGNALING 0.3217594287398594 7316-878 +BS_J483EMFP HALLMARK_PROTEIN_SECRETION 0.20157452602451797 7316-878 +BS_J483EMFP HALLMARK_REACTIVE_OXIGEN_SPECIES_PATHWAY 0.34052071009270024 7316-878 +BS_J483EMFP HALLMARK_SPERMATOGENESIS 0.29502342224512407 7316-878 +BS_J483EMFP HALLMARK_TGF_BETA_SIGNALING -0.3412773840953336 7316-878 +BS_J483EMFP HALLMARK_TNFA_SIGNALING_VIA_NFKB 0.25940935554299804 7316-878 +BS_J483EMFP HALLMARK_UNFOLDED_PROTEIN_RESPONSE 0.45922881022769985 7316-878 +BS_J483EMFP HALLMARK_UV_RESPONSE_DN -0.1882935035024666 7316-878 +BS_J483EMFP HALLMARK_UV_RESPONSE_UP 0.3258169861241061 7316-878 +BS_J483EMFP HALLMARK_WNT_BETA_CATENIN_SIGNALING -0.04377685507730042 7316-878 +BS_J483EMFP HALLMARK_XENOBIOTIC_METABOLISM 0.08374023069310477 7316-878 +BS_K25F4J3V HALLMARK_ADIPOGENESIS -0.25750273894577586 7316-386 +BS_K25F4J3V HALLMARK_ALLOGRAFT_REJECTION -0.5498996921649709 7316-386 +BS_K25F4J3V HALLMARK_ANDROGEN_RESPONSE -0.2638230404429326 7316-386 +BS_K25F4J3V HALLMARK_ANGIOGENESIS -0.35591100940738607 7316-386 +BS_K25F4J3V HALLMARK_APICAL_JUNCTION -0.3252426625417125 7316-386 +BS_K25F4J3V HALLMARK_APICAL_SURFACE -0.20145604709725337 7316-386 +BS_K25F4J3V HALLMARK_APOPTOSIS -0.42693188555120093 7316-386 +BS_K25F4J3V HALLMARK_BILE_ACID_METABOLISM -0.1857077721602655 7316-386 +BS_K25F4J3V HALLMARK_CHOLESTEROL_HOMEOSTASIS -0.23301789680772006 7316-386 +BS_K25F4J3V HALLMARK_COAGULATION 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HALLMARK_ESTROGEN_RESPONSE_LATE -0.41671942745221546 7316-1781 +BS_WVW3W6ZB HALLMARK_FATTY_ACID_METABOLISM 0.06827275215425807 7316-1781 +BS_WVW3W6ZB HALLMARK_G2M_CHECKPOINT 0.5282958084707391 7316-1781 +BS_WVW3W6ZB HALLMARK_GLYCOLYSIS 0.13476910806870324 7316-1781 +BS_WVW3W6ZB HALLMARK_HEDGEHOG_SIGNALING -0.30575643697944926 7316-1781 +BS_WVW3W6ZB HALLMARK_HEME_METABOLISM -0.1805685705404848 7316-1781 +BS_WVW3W6ZB HALLMARK_HYPOXIA -0.27450137452888806 7316-1781 +BS_WVW3W6ZB HALLMARK_IL2_STAT5_SIGNALING -0.3255672842452306 7316-1781 +BS_WVW3W6ZB HALLMARK_IL6_JAK_STAT3_SIGNALING -0.5041725395965997 7316-1781 +BS_WVW3W6ZB HALLMARK_INFLAMMATORY_RESPONSE -0.48427503687476287 7316-1781 +BS_WVW3W6ZB HALLMARK_INTERFERON_ALPHA_RESPONSE -0.4532476644982686 7316-1781 +BS_WVW3W6ZB HALLMARK_INTERFERON_GAMMA_RESPONSE -0.4797838490755645 7316-1781 +BS_WVW3W6ZB HALLMARK_KRAS_SIGNALING_DN -0.2522047460161186 7316-1781 +BS_WVW3W6ZB HALLMARK_KRAS_SIGNALING_UP -0.4263917024000838 7316-1781 +BS_WVW3W6ZB HALLMARK_MITOTIC_SPINDLE 0.09149622956990847 7316-1781 +BS_WVW3W6ZB HALLMARK_MTORC1_SIGNALING 0.29102041577884386 7316-1781 +BS_WVW3W6ZB HALLMARK_MYC_TARGETS_V1 0.6571536461872055 7316-1781 +BS_WVW3W6ZB HALLMARK_MYC_TARGETS_V2 0.5926140344169164 7316-1781 +BS_WVW3W6ZB HALLMARK_MYOGENESIS -0.3630766665561542 7316-1781 +BS_WVW3W6ZB HALLMARK_NOTCH_SIGNALING -0.09018203579506653 7316-1781 +BS_WVW3W6ZB HALLMARK_OXIDATIVE_PHOSPHORYLATION 0.39746749718862634 7316-1781 +BS_WVW3W6ZB HALLMARK_P53_PATHWAY -0.15869310055874486 7316-1781 +BS_WVW3W6ZB HALLMARK_PANCREAS_BETA_CELLS -0.3730600182518411 7316-1781 +BS_WVW3W6ZB HALLMARK_PEROXISOME 0.12336853553573665 7316-1781 +BS_WVW3W6ZB HALLMARK_PI3K_AKT_MTOR_SIGNALING 0.08556838233378139 7316-1781 +BS_WVW3W6ZB HALLMARK_PROTEIN_SECRETION 0.3259057897543175 7316-1781 +BS_WVW3W6ZB HALLMARK_REACTIVE_OXIGEN_SPECIES_PATHWAY -0.09094491002911281 7316-1781 +BS_WVW3W6ZB HALLMARK_SPERMATOGENESIS 0.041580065924517184 7316-1781 +BS_WVW3W6ZB HALLMARK_TGF_BETA_SIGNALING -0.034274183052556195 7316-1781 +BS_WVW3W6ZB HALLMARK_TNFA_SIGNALING_VIA_NFKB -0.4384092370771124 7316-1781 +BS_WVW3W6ZB HALLMARK_UNFOLDED_PROTEIN_RESPONSE 0.4099526229734882 7316-1781 +BS_WVW3W6ZB HALLMARK_UV_RESPONSE_DN -0.3058514184534369 7316-1781 +BS_WVW3W6ZB HALLMARK_UV_RESPONSE_UP -0.09190203193194285 7316-1781 +BS_WVW3W6ZB HALLMARK_WNT_BETA_CATENIN_SIGNALING 0.008011422921919087 7316-1781 +BS_WVW3W6ZB HALLMARK_XENOBIOTIC_METABOLISM -0.056606893714397144 7316-1781 +BS_WWKNJSJ5 HALLMARK_ADIPOGENESIS -0.21049470276204024 7316-3680 +BS_WWKNJSJ5 HALLMARK_ALLOGRAFT_REJECTION 0.263258648989657 7316-3680 +BS_WWKNJSJ5 HALLMARK_ANDROGEN_RESPONSE -0.08345767869753043 7316-3680 +BS_WWKNJSJ5 HALLMARK_ANGIOGENESIS 0.24343945565682484 7316-3680 +BS_WWKNJSJ5 HALLMARK_APICAL_JUNCTION 0.20240941379777017 7316-3680 +BS_WWKNJSJ5 HALLMARK_APICAL_SURFACE -0.04282477783112751 7316-3680 +BS_WWKNJSJ5 HALLMARK_APOPTOSIS 0.22224574547094827 7316-3680 +BS_WWKNJSJ5 HALLMARK_BILE_ACID_METABOLISM -0.17009491521821957 7316-3680 +BS_WWKNJSJ5 HALLMARK_CHOLESTEROL_HOMEOSTASIS 0.018043656064822305 7316-3680 +BS_WWKNJSJ5 HALLMARK_COAGULATION 0.26673026763876057 7316-3680 +BS_WWKNJSJ5 HALLMARK_COMPLEMENT 0.31872533192024893 7316-3680 +BS_WWKNJSJ5 HALLMARK_DNA_REPAIR -0.06775254339278869 7316-3680 +BS_WWKNJSJ5 HALLMARK_E2F_TARGETS -0.33521523663363745 7316-3680 +BS_WWKNJSJ5 HALLMARK_EPITHELIAL_MESENCHYMAL_TRANSITION 0.5203009307990152 7316-3680 +BS_WWKNJSJ5 HALLMARK_ESTROGEN_RESPONSE_EARLY 0.21604509047685594 7316-3680 +BS_WWKNJSJ5 HALLMARK_ESTROGEN_RESPONSE_LATE 0.15885776144833358 7316-3680 +BS_WWKNJSJ5 HALLMARK_FATTY_ACID_METABOLISM -0.17817710225316535 7316-3680 +BS_WWKNJSJ5 HALLMARK_G2M_CHECKPOINT -0.1834682793808526 7316-3680 +BS_WWKNJSJ5 HALLMARK_GLYCOLYSIS 0.19323574801153198 7316-3680 +BS_WWKNJSJ5 HALLMARK_HEDGEHOG_SIGNALING -0.10639466430007148 7316-3680 +BS_WWKNJSJ5 HALLMARK_HEME_METABOLISM -0.012761397776174688 7316-3680 +BS_WWKNJSJ5 HALLMARK_HYPOXIA 0.5318992930398504 7316-3680 +BS_WWKNJSJ5 HALLMARK_IL2_STAT5_SIGNALING 0.31852238168677144 7316-3680 +BS_WWKNJSJ5 HALLMARK_IL6_JAK_STAT3_SIGNALING 0.36873286932569643 7316-3680 +BS_WWKNJSJ5 HALLMARK_INFLAMMATORY_RESPONSE 0.46425978301401655 7316-3680 +BS_WWKNJSJ5 HALLMARK_INTERFERON_ALPHA_RESPONSE 0.1464317230918195 7316-3680 +BS_WWKNJSJ5 HALLMARK_INTERFERON_GAMMA_RESPONSE 0.25521827400025915 7316-3680 +BS_WWKNJSJ5 HALLMARK_KRAS_SIGNALING_DN 0.014255052769771404 7316-3680 +BS_WWKNJSJ5 HALLMARK_KRAS_SIGNALING_UP 0.15067802150808038 7316-3680 +BS_WWKNJSJ5 HALLMARK_MITOTIC_SPINDLE -0.16713601432625447 7316-3680 +BS_WWKNJSJ5 HALLMARK_MTORC1_SIGNALING 0.08728381233753907 7316-3680 +BS_WWKNJSJ5 HALLMARK_MYC_TARGETS_V1 -0.1364018560446702 7316-3680 +BS_WWKNJSJ5 HALLMARK_MYC_TARGETS_V2 0.23183789498730867 7316-3680 +BS_WWKNJSJ5 HALLMARK_MYOGENESIS 0.2876525988455338 7316-3680 +BS_WWKNJSJ5 HALLMARK_NOTCH_SIGNALING -0.19155525139688925 7316-3680 +BS_WWKNJSJ5 HALLMARK_OXIDATIVE_PHOSPHORYLATION -0.4779170702567086 7316-3680 +BS_WWKNJSJ5 HALLMARK_P53_PATHWAY 0.24155928049590386 7316-3680 +BS_WWKNJSJ5 HALLMARK_PANCREAS_BETA_CELLS -0.16705553931385284 7316-3680 +BS_WWKNJSJ5 HALLMARK_PEROXISOME -0.21169739056749956 7316-3680 +BS_WWKNJSJ5 HALLMARK_PI3K_AKT_MTOR_SIGNALING 0.021755248729081383 7316-3680 +BS_WWKNJSJ5 HALLMARK_PROTEIN_SECRETION -0.2922455426440786 7316-3680 +BS_WWKNJSJ5 HALLMARK_REACTIVE_OXIGEN_SPECIES_PATHWAY 0.3708878461021191 7316-3680 +BS_WWKNJSJ5 HALLMARK_SPERMATOGENESIS -0.06204245939446809 7316-3680 +BS_WWKNJSJ5 HALLMARK_TGF_BETA_SIGNALING -0.04451087841000406 7316-3680 +BS_WWKNJSJ5 HALLMARK_TNFA_SIGNALING_VIA_NFKB 0.5786361112803337 7316-3680 +BS_WWKNJSJ5 HALLMARK_UNFOLDED_PROTEIN_RESPONSE 0.051282634888155515 7316-3680 +BS_WWKNJSJ5 HALLMARK_UV_RESPONSE_DN 0.04950066790191909 7316-3680 +BS_WWKNJSJ5 HALLMARK_UV_RESPONSE_UP 0.10374836998306639 7316-3680 +BS_WWKNJSJ5 HALLMARK_WNT_BETA_CATENIN_SIGNALING 0.03126143137691623 7316-3680 +BS_WWKNJSJ5 HALLMARK_XENOBIOTIC_METABOLISM 0.2653585477242154 7316-3680 diff --git a/analyses/molecular-subtyping-ATRT/plots/atrt_heatmap.png b/analyses/molecular-subtyping-ATRT/plots/atrt_heatmap.png index ddd23fd88f..0c49898ad4 100644 Binary files a/analyses/molecular-subtyping-ATRT/plots/atrt_heatmap.png and b/analyses/molecular-subtyping-ATRT/plots/atrt_heatmap.png differ diff --git a/analyses/molecular-subtyping-ATRT/results/ATRT_molecular_subtypes.tsv b/analyses/molecular-subtyping-ATRT/results/ATRT_molecular_subtypes.tsv index 9742e31ee1..17b0f52c50 100644 --- a/analyses/molecular-subtyping-ATRT/results/ATRT_molecular_subtypes.tsv +++ b/analyses/molecular-subtyping-ATRT/results/ATRT_molecular_subtypes.tsv @@ -1,33 +1,33 @@ -sample_id Kids_First_Biospecimen_ID Kids_First_Participant_ID age_at_diagnosis_days OS_months germline_sex_estimate primary_site location_summary chr_22q_loss SMARCB1_focal_status TYR MITF DCT VEGFA DNAH11 SPEF1 POU3F4 POU3F2 PBX1 SMARCA4_focal_status HALLMARK_NOTCH_SIGNALING MYCN GLI2 CDK6 ASCL1 ZBTB7A MYBL2 MXI1 MEIS3 MEIS2 MAX INSM1 FOXK1 HALLMARK_MYC_TARGETS_V1 HALLMARK_MYC_TARGETS_V2 ATF4 RAD21 IRF9 CEBPB MYC STAT1 TCF7L2 REST IRF8 NR4A2 FOXC1 RARG HOTAIR tmb -7316-1073 BS_PGHK1JRW, BS_W23ERYW3 PT_TV5DYHNC 1113 Male Thalamus supratentorial No loss -0.5347967888204088 -0.013825621239973412 -0.3443657853337286 -0.6734435096585513 -0.7984422683741907 -0.6296701265532815 0.6203025194004408 0.1669110631712864 0.23648763136783643 neutral -1.0130975957540014 -0.5521577769470015 0.27575506920874937 -0.01265847013662434 -0.2896007762851814 1.3077250430155445 -0.29840698598088833 0.3218074884749238 -0.13367951927160035 -1.3377232216976231 0.01559477691372188 -0.7394917479106412 -0.5470179894558204 -0.12146802405954313 0.25972048535904974 -0.28877598822632367 -0.8329465607114955 0.6678205496625225 1.0516612060706723 0.7374646450034709 0.02287497406701431 1.3832901270133175 0.5627413450941386 2.021664623709324 -0.6713969108985504 0.9102193105115808 0.40989791050715685 0.5126213869336954 0.22402644019285903 -7316-1137 BS_GAGRGSSX PT_4J24F353 575 36.1315068493151 Frontal Lobe supratentorial NA NA -0.5415019988009669 -0.30427262549641976 -0.5169215190120005 0.05477176202762979 -0.578727833381572 -0.7237637477441374 -0.7111711546846468 -0.7904135552065453 -1.4318099369836728 NA -0.8361390640100016 -0.9476455291041406 0.18424291701098022 -1.4270609955326057 -0.8327022392213496 0.8503428667139021 0.5515479805369379 -1.3708886778586935 -0.7960714389584417 -0.2772920186475043 1.4787167328988868 -0.7826973317696674 0.26151541605131634 0.1459328779289413 0.442352132643609 -0.46861735795051745 -0.723246686317995 1.210641182652257 1.44525231401883 0.8133184879230186 1.3682194312785556 1.1796091200413312 0.37179490231102585 1.7034838787407744 -0.10571482879636605 1.0745767003192424 1.2494921359405216 -0.5190412250372987 NA -7316-122 BS_DHA5FMVW, BS_QMHND3QK PT_ND34A6PR 2982 87.3205479452055 Female Parietal Lobe supratentorial No loss -0.5415019988009669 0.7484966127380674 1.7766358127743929 -1.4897936634740059 -0.553349043525155 -0.4823260271446828 -0.7255963696006936 -0.8146664314337252 -0.4392987662112909 loss -1.395425116242621 -0.9429888031702961 -0.6736721764907859 0.8057045259505096 -0.9259006994000688 0.5526707657533713 0.1033498294774459 -0.07473066118135181 1.369649382902332 0.513531379823246 0.6599367994171083 -0.9972334663157562 -0.8881267951428878 0.43775579386927993 0.5701717163684301 0.7996804058393929 -0.6192169771249938 0.6030160875511333 0.2320192873854527 0.8253420065513858 0.8584968559371662 0.4814973016676753 0.5587085574199787 0.28464368805813783 0.5296869782435116 0.9773430568272997 1.434527495749422 0.9260253112229148 1.8346226338847265 -7316-1771 BS_859AV1DB, BS_MVW01FPB PT_3KM9W8S8 190 17.1945205479452 Female Other locations NOS;Spinal Cord- Lumbar/Thecal Sac;Spinal Cord- Thoracic;Temporal Lobe "NA" No loss -0.5415019988009669 -0.9248221624600625 -0.5611356553218738 0.09004306683371797 -0.39788590070967844 -0.4182248611089406 2.095874561470534 1.8355696612985868 1.032857385702953 loss 0.7724520428494224 1.099354333031074 -0.15299500640483402 -1.4685603986338047 0.039547427050308066 -0.7857850219621203 0.5386601611145514 0.23218783335997353 0.6286277908833712 1.1004422813848544 -1.1685625681054121 0.2774595893165802 2.5149393960233786 0.566377269345382 0.26527118054787735 1.2381207027950765 0.42842420518766783 -0.9811020625415463 -0.2066538706083959 -0.11549853188374676 -1.0860748239510234 0.3085017962352559 -0.08601577732613293 -0.7055652340330063 -1.2660568226851399 -1.0633853532025674 -0.6640292653278335 -0.5979814635908083 0.2130816370078644 -7316-1778 BS_B1HVNV0T, BS_WCNPE0AC PT_FYECBRPP 562 29.4575342465753 Male Brain Stem- Midbrain/Tectum;Ventricles infratentorial Yes loss -0.5415019988009669 -0.8331797433220036 0.03156944821735099 -0.917531433916074 -0.09911341823268521 0.8453624497486465 1.0481352558848616 0.8853179711041873 1.0214321330772236 neutral -0.4586021793230046 -0.18006026721835652 -0.9591934910764467 -1.530067435790284 -0.07695117990721823 0.33151978662405696 -2.482603824867588 0.3056903880841108 0.6535122777048821 0.25620703224224134 -0.35936143221144706 0.5572898522508025 -0.5662504536842731 -2.135198271522666 -2.8539321151398367 -2.1332552194229133 0.43133290726876733 1.8866165966733555 -0.4918767418361243 -1.4274899865310795 2.0198217227789823 -0.4856925280403716 -2.114298759907974 -0.19807161187049288 -0.07873182658536003 -0.4865707852650271 -1.582873166533823 -0.5979814635908083 0.17203862506413448 -7316-1781 BS_0EN5R1AP, BS_WVW3W6ZB PT_M1RYN7B0 1038 14.2356164383562 Male Frontal Lobe supratentorial No loss 1.3716622497068833 1.0571301099300077 -0.4741814649464887 -0.6805114246123781 -0.7691960159473054 0.32936356006209255 0.37867531720135506 1.356229073905715 -1.4076472730915286 neutral 0.15587605467138724 0.8145296192415123 0.5638666152998215 0.6841102521077866 1.3282017140255198 -0.48733954261471074 0.39149604022394235 -0.9563117104840939 0.4085336559052065 1.7129169231656056 -0.6693591369414116 -0.6215372370570414 0.41190593170086187 0.5616307126325519 0.3913476952927525 -0.8517050596165492 0.6983231297515029 0.8587681050568556 -1.3013084839519884 -0.590040642989226 0.5300067829910701 0.22937290802730903 0.8475779149857451 -1.1990700971028612 -0.10875159349892773 -1.431764508848882 0.781321163603894 -0.5979814635908083 0.2924314600990755 -7316-1790 BS_A94A7EJ4, BS_MV6ASWV9 PT_ESHACWF6 1506 19.0684931506849 Female Cerebellum/Posterior Fossa infratentorial No loss -0.5347967888204088 -0.6353069633158734 -0.28861426731137907 0.7127821695631376 -0.12745973403649913 -0.03365631109533356 1.0695274094072391 1.0261570449223691 0.7583689144273025 neutral 1.0648609858355291 1.0436230683914787 -0.012324792435626446 -1.2667497394979899 1.4006508400121969 -1.5793762844387964 1.9475483281958104 -0.5600218365911476 -1.0013996303559844 -0.7047767426727248 0.12808986123205415 0.38498828061676393 1.2447695010872768 0.7658210341147461 0.7397801246286309 -0.15229822342325253 -0.3682366803219983 -1.8455827343175428 -0.3953207291818689 -2.4149458871822578 -0.2684705609021571 -1.6824210228639063 -0.6046513117239766 -1.0542108908898522 -1.1134123082255345 -0.9012963254925611 -0.33394137075618874 0.08044759853277893 4.654619579518502 -7316-2090 BS_19EJ85F8 PT_T5KEXCK7 1026 7.52876712328767 Female Brain Stem- Pons;Cerebellum/Posterior Fossa infratentorial No neutral NA NA NA NA NA NA NA NA NA neutral NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA 0.37417545888700426 -7316-2110 BS_4E1G7E3G, BS_6GN1FGTB PT_RJ1TJ2KH 218 13.413698630137 Male Cerebellum/Posterior Fossa infratentorial Yes loss 1.895050517456976 1.7236518902599738 0.19120536836753946 1.3589522097278677 1.837672570575437 1.074764559372531 -0.6428996491136019 -0.5058236915925419 0.34224674023671947 loss -1.4541775410025324 1.5863383072812351 0.8117646387142791 -0.016114426634444748 0.76625184279659 1.6610176580148857 0.8875852683547192 1.9233281337081094 -0.6086302760463277 0.6839632247652988 1.7637137787738673 0.969364884593295 0.1458042683998447 -1.5456478124932589 -0.689021224533351 -1.2914719863769237 0.8105386426377619 1.1358458238088829 -0.8398947809294176 0.21607486631785178 -0.8915668523620124 1.1914069324156498 1.4766523977911539 -0.8405007465416791 -0.15843981321578923 -0.3426433098362721 -0.2560729812810232 -0.5979814635908083 0.12176093543306536 -7316-2141 BS_8WJR4AA3, BS_MMNRZ1EQ PT_WG2Z95B5 383 33.6 Male Parietal Lobe;Temporal Lobe supratentorial No loss -0.33927110435099267 -0.699265956261734 -0.3927520141336199 -0.45738212506357195 -0.5283829352539844 -0.9687233718327408 -0.7111711546846468 -0.5753384122774502 -1.0122003424083235 neutral -1.3561985169806845 -1.1568726445919153 -0.17866547198452995 0.06287292232117529 -0.8587282462045184 -1.2096199633707727 0.8008740840771239 -1.3080135627871163 1.3595785065997308 0.6557411671489045 -2.3169933757659122 -0.9972334663157562 -0.8727801453727876 0.6303295886167647 0.7791317763751984 0.3218947309133199 0.0013567326699894114 0.3613704558231209 -0.0786106435502567 0.9901191046485864 0.8157272543390651 -0.4031498590658478 -0.4822284700422686 0.1860757962550865 -1.1205909783273371 -0.9414585698266094 0.027488328345849702 0.8767559736137422 0.2715679290276795 -7316-2181 BS_KXCY5BN5, BS_NDSWS9TS PT_GH693TT8 738 32.4493150684931 Male Cerebellum/Posterior Fossa;Spinal Cord- Cervical;Spinal Cord- Lumbar/Thecal Sac;Spinal Cord- Thoracic infratentorial Yes loss 1.2927352144239614 1.6285162451019226 1.0609766821813307 0.1214003877834167 0.9127574765456168 1.767326331847199 -0.7255963696006936 -0.9212811043213547 -0.07093567531192875 loss 0.555115775494888 0.37793947700911384 -0.9672865079914718 0.8460148151084552 0.9253222435773343 -0.0797027748461212 0.08756163676475674 0.0754755012091715 -1.380675127378444 -1.9216155679249654 0.22818042993803386 0.17352286654579982 -0.055859886842995754 0.480876663302207 0.16407555355942186 -1.155238752498207 0.9824761543256104 0.2461076162745762 -1.0991579115473202 -0.5836917955116351 0.04070329994083773 -0.2199748443150664 0.4474695767373233 -0.005594554071533386 -0.06987360413998189 0.03914579685379103 -0.35750811548637934 -0.5063204041563798 0.16143584697867094 -7316-2186 BS_6G6C7VPX, BS_NXZSD2KK PT_XTVQB9S4 291 11.441095890411 Female Frontal Lobe;Meninges/Dura;Parietal Lobe;Spinal Cord- Cervical;Spinal Cord- Lumbar/Thecal Sac;Spinal Cord- Thoracic;Temporal Lobe;Ventricles "NA" Yes loss 2.5628523499657923 1.843356976652882 3.6099441036529463 1.456306632805449 1.8821037408764822 1.8563446672552735 -0.7477628560317484 -0.994229531504657 -0.2759083206527736 neutral 0.23211607542468987 0.0019379156208071849 -1.2669634980502094 0.6917692263199998 0.24997082137385132 -0.39160424342396616 0.292664187697996 -0.19165494278022124 -1.2073853131859227 -1.5731155229592408 -0.457958387609509 -0.5131738737534667 0.0817253309089881 0.6888045257310009 0.6640405405553332 -0.818946379049364 0.7356410265011725 -0.6388309403395951 -0.5642081510625491 0.03960933987205409 -0.275817598305451 -0.3782846624482021 0.6169159896148945 -1.366297778010545 0.1831737461905995 -1.2198845374036331 -0.241552365337394 -0.5979814635908083 0.1819573529505359 -7316-2187 BS_53TV75NN, BS_850BAHH9 PT_HVZTF42R 170 11.9013698630137 Female Frontal Lobe;Parietal Lobe;Temporal Lobe supratentorial No neutral -0.5415019988009669 -0.5843815265178426 -0.654419178592843 -0.5369217313540176 -0.858661038657048 -0.9796084721152905 1.0903318435190192 0.26677073163353804 1.0775175010179487 neutral 1.9148437865696675 -0.8076460657641753 0.6263437821054239 0.3722056472928659 -0.2917804318694729 -0.4064729426183324 -0.43937428984630916 -1.5051982797213062 -0.7155496976248928 0.2206103598071793 0.16750006637040388 -0.7394917479106412 -0.14238299596451046 0.5679214952268719 0.3161747500519027 0.04559935307640895 -0.5647198661035296 0.03451423515879915 0.18823018035927203 0.5004087119187005 0.32463923756121504 -0.4517463790994928 0.053727350407683845 0.7496767094318617 1.6416368666179932 1.4626147435064678 -0.24240060549159867 -0.5979814635908083 0.19598038203131027 -7316-2224 BS_P7EY9DXG, BS_SCQNN2A2 PT_H8Z52K09 624 4.10958904109589 Male Frontal Lobe;Parietal Lobe supratentorial No loss -0.5415019988009669 -0.6900998227442469 -0.4847336470721381 0.09953200853482401 -0.4440662789335005 0.021040588321809554 0.7993199503205048 1.932356990948393 1.8802512356214123 neutral 1.3089639869417233 1.8719077786024385 1.4588207754625968 1.274825994339568 2.016287730116499 -1.9272341324030942 0.5325441672196368 0.6642546677417376 -1.6576800505522877 1.395191451780788 0.06053399184019198 1.5323272032552617 -0.025453162382042517 0.7083002683226592 0.12208361041200538 1.1803113961177618 1.6717249058472394 0.3492234170996536 -0.25155200610246686 -1.2571928179138336 0.7165625054483625 0.1648934833144225 -0.4320064946924242 -0.8659418726704721 0.7841561444993662 -0.7987815158212331 -1.3043306203359966 -0.5845011785378568 0.24728414696097265 -7316-2269 BS_9FHSNVS0, BS_ZAT0XJE5 PT_JV9G8MFD 362 28.0767123287671 Female Frontal Lobe supratentorial No neutral -0.5281576410959825 -0.005839787071674717 0.13364584683675595 1.6325550902360912 1.125027229078876 0.24710031539898739 1.7372686428070536 1.6142232346562555 1.4618097065581626 neutral -0.32666135637778243 1.6805096628569318 2.7599489066245018 1.5204974704602836 1.5328870626811761 0.9378758918494249 -0.40552095489149526 2.2352094754206426 -0.03933251987347904 2.355080149795731 0.8193497179258852 1.8024699974266516 1.5345462402389154 -1.6431556909748 -1.113505661619769 0.718811808371843 0.18695265825053578 1.4842300985592451 -0.26909617923287 -0.8097865955493722 0.05638621752021236 1.3456610896769725 0.7240008324642764 0.06836340948515807 -0.4163868361928942 -0.6134520978030628 -1.1800116429588463 -0.5979814635908083 0.16690824857116826 -7316-2276 BS_0FQKT8EY, BS_996ZS2A4 PT_RX1EWBP9 1351 21.0082191780822 Female Frontal Lobe supratentorial No neutral -0.5415019988009669 -0.6002901222780674 -0.654419178592843 -0.41813769276491247 -0.553349043525155 -0.7690234201866005 -0.7111711546846468 0.17862269508879114 -0.4733288345591142 neutral -0.1537966446501526 -0.6148902994516384 -0.3352021447765901 -0.6859502715667178 -0.5524712920419003 -0.3621358303446223 0.6545153285950011 -1.6890245019552415 0.9803840374651966 -0.7820981464795177 -0.2598333912976048 -0.5318886296189185 0.3222214327448128 0.5644190888857256 0.6494797088541671 0.9922399683178024 -0.2560503250871343 0.3635698772006503 0.5790587608249225 0.2678463537801695 0.947716298933317 -0.4169779159166965 0.09933258096721487 0.9553157361920838 -0.47721437973285824 -1.2540951322060832 -0.001965009970484819 0.6912841524758266 2.5901560787488878 -7316-2582 BS_1C4WCNQF, BS_GJNCYABP PT_7MZRW1DH 5688 23.2109589041096 Female Frontal Lobe supratentorial No loss -0.5415019988009669 0.26230259145211443 -0.5953265586334711 -2.030705146562924 -0.7691960159473054 -0.4750372101917142 -0.6900358047339231 -0.23813378796865695 -1.133227557815281 neutral 0.529715283334208 -1.1324707986484117 -0.9471849703645285 -0.27493728169811193 -0.9623419682608354 0.2404341261643897 -0.6321394776708358 -0.4563220945088413 0.20221125191917733 -0.5310728674630087 0.6422285411342491 -0.6427937458138188 -0.6466691987535979 0.3242213330690228 0.09208342836290549 0.05949479714345009 0.3054229777152252 1.3050239819331901 2.022011900658915 0.3133138809857567 1.3943164768386094 -0.8569999982905329 0.08782367569531396 1.936499376711231 0.9630524765233464 1.7020515002590344 0.6668117239192128 -0.43240621268392443 1.019918846801688 -7316-2688 BS_JDMM2XG4, BS_WV0S8N4M PT_32J909WM 860 28.7342465753425 Male Cerebellum/Posterior Fossa;Ventricles infratentorial No loss 1.2344634201543843 1.7063263229107868 0.6270500894144933 -0.3625945502101911 1.6873522179432607 2.5174676381007064 -0.4635386931772721 -0.5121489435133498 -0.1317358968006712 neutral 1.15691772187971 -0.4062850496852571 -0.9878337921162526 0.5032299914264298 0.21149467482405568 0.5211453078793469 -0.6581686841728105 0.30065893082062545 -1.1597610691988773 -0.44726949436031027 -0.3546008172152849 -0.19555250124945853 -0.5958382766939943 0.3207075222575796 -0.6589116570568834 -1.1878555461495197 -0.1449824729757427 0.47115555030573986 -0.23289453186590153 -0.5972376276371735 0.26163155143641675 -0.5355530955009137 0.26079786303513613 0.5676967480407455 -0.3034431382262901 -0.5365764835346232 -0.5567206326907949 -0.5979814635908083 0.1696444493674169 -7316-2933 BS_74FS6GMW, BS_DE26D072 PT_XTVQB9S4 291 11.441095890411 Female Basal Ganglia;Temporal Lobe supratentorial No loss -0.5281576410959825 -0.9942499612046696 -0.3829275760921679 0.6855158461692943 2.165896307619269 0.743975230457378 0.7085413676912112 1.3235171971029347 0.7902137808621955 loss 1.1463152487250614 0.7154810316463506 0.556046783689436 1.3611704697947857 0.18103273589626126 -0.9231426341592086 0.8081087452210951 0.20168529121560233 1.451458738496155 0.36445287915777 -1.4282950526210103 0.4371766750120919 -0.35226371380495114 0.7690766384634262 0.8565106938857731 1.1365271698760528 1.2283369368992183 -1.4725958509845416 -0.8715361666695406 0.9585763738762982 -0.8954898789623922 1.3046280480725712 0.23330239268167519 -1.2450228177589822 -1.2103449253435647 0.14367832052376034 -0.9758296147980352 -0.5579364554478906 1.6095701183932742 -7316-3045 BS_983Z6CA6 PT_3KM9W8S8 190 17.1945205479452 Female Other locations NOS;Spinal Cord- Lumbar/Thecal Sac;Spinal Cord- Thoracic;Ventricles infratentorial NA NA -0.5215832665770787 -0.8643832517894658 -0.4953734001749602 1.5878736215769753 0.9557414235673398 0.9619784930226518 -0.5168917983911031 -0.3692521264066576 -0.19361973014348052 NA -1.1923966962321175 0.49723354607002684 -0.7285553260610074 -1.4411932996350094 -0.5459322743356074 1.045341201836939 -1.6978082966310328 0.7878781111986574 0.6074354536563664 0.7110462473243825 0.6824699308986566 -0.9811424395926222 -0.693863799796413 -2.2793285282991294 -1.560467210161915 0.138674626375691 -1.7842476039857946 -0.4946371865360517 0.8689419539273682 0.2629706559775337 -1.821444901638292 -0.5498784822529503 -0.5314217077855774 0.608129971709433 1.6054985098685617 0.33806729149865966 -0.15013022175256563 -0.4937179182076291 NA -7316-3680 BS_6VKKMM6M, BS_WWKNJSJ5 PT_RJ1TJ2KH 218 13.413698630137 Male Cerebellum/Posterior Fossa infratentorial Yes loss 1.5760789003486937 0.37060992198387444 0.4456359215680595 2.1430549823003644 0.41348236614193956 -0.5044540973125771 -0.5863114414212781 -0.596565412922691 -0.04878797679629697 neutral -0.372974251120966 0.5307594906712975 0.019041556020645507 -0.2546428654739587 -0.6634735835924094 -0.480497387505843 -1.7426545793919104 1.011411243827036 -0.27869975675589503 -0.6640825380244667 0.8508911097188988 -0.6427937458138188 -0.5593056991601241 -1.2909110172002911 -0.7479570826482759 0.19274227731118992 -1.8713780132861888 0.588601195889576 2.517634806514237 0.45257156955850814 -1.2408385469026995 -0.9914555711222524 -0.1905454228247364 0.8448985525308699 0.6439577056930699 -0.19117466934445818 -0.5370546853989747 -0.3852794620626462 1.1810126686808278 -7316-376 BS_74A1TB03, BS_M4923M40 PT_MTE126WM 1923 56.8438356164384 Female Cerebellum/Posterior Fossa;Other locations NOS infratentorial NA loss -0.5415019988009669 -1.1527221319582008 -0.654419178592843 -0.1477635704749153 -0.858661038657048 -0.7782777772413161 -0.7552982503965977 -1.0338338828361482 0.3638395271186248 loss -0.43199528336915916 -1.2284615315863612 -0.08625427118578567 0.13818962051392478 -0.9142022310443233 -0.9811642476588933 0.41214501284665217 0.5285173688991244 0.39954206623176775 -1.4146263617640142 -0.8241306619852391 -0.9345989497865101 0.381159917509929 0.62845069889062 0.8829711216246239 0.9591970157816565 0.16524286383742273 -0.4483432498191703 -0.7310490382214565 1.0736463113632155 -0.7249677138458908 2.89374887724261 1.5982906363249538 -0.9781993156157253 -1.1646102211703953 1.2604103053464724 2.372191203923612 1.8518112571996523 0.2773823557197079 -7316-386 BS_GTAJFTTR, BS_K25F4J3V PT_J302B8Y5 826 8.94246575342466 Male Cerebellum/Posterior Fossa infratentorial Yes loss -0.5022364437079205 -0.6145036988386084 -0.5611356553218738 -0.7513892477457589 -0.386554618071306 -0.581214861580421 2.649291831611998 1.2372983660187467 1.7365202009642031 neutral 1.031001680684533 1.783781786479442 1.965537710603289 1.5340247540023426 1.9155391686915413 -1.0170765640014785 0.8757589320571514 0.6174841447110246 -1.1417999926217655 1.2454063634420267 -0.6976511796539998 1.5681219481442576 3.050903030693486 0.6362802632760546 0.327920925968157 -1.2617616121256112 1.5550143344176832 -1.8894645076384873 -1.7499038825483515 -1.694250881669251 -1.3535787376585566 0.4015530097216381 0.6247007917383914 -0.8513311119141677 -1.1571580761181612 -1.2590718345935297 -0.817467897678064 -0.5979814635908083 0.3454453505263933 -7316-3890 BS_5WK2KXYW, BS_S71RJ8DH PT_E6FTW238 557 6.54246575342466 Female Cerebellum/Posterior Fossa infratentorial Yes loss -0.5281576410959825 -0.7719941975861001 -0.3443657853337286 -0.8131480447477902 -0.6984285674889333 -0.12325917097023086 -0.6494564076945695 -0.6846222597125535 0.26145010847142724 loss -0.10997127812995068 -1.0110187699275124 0.8347185829674478 0.5361575893303322 -0.812620306957091 -0.5201042927741156 -0.09437668717429494 -0.28696942399186054 1.1557907403442162 -0.0776361931944017 0.6733338065739144 0.268173146885313 0.18351360170791547 0.2131897392414147 0.23139116898320392 -0.7900756813312243 -0.17298711335755426 0.041147351063792116 -0.6246375674049776 0.584860007412991 0.14497429670078738 -0.23064970392888093 0.26800206445792746 0.06525054483050716 -1.0106900350815275 1.7893390039913235 1.4795346970671344 3.1505617951137332 0.2883271589047025 -7316-3920 BS_E0S2Y0TS PT_6N825561 1564 65.6876712328767 Female Temporal Lobe supratentorial Yes loss NA NA NA NA NA NA NA NA NA neutral NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA 1.8014461992302115 -7316-3937 BS_QX12J6W1, BS_R5G3QP11 PT_XRQHMBHB 2841 20.2191780821918 Male Cranial Nerves NOS supratentorial No loss -0.5347967888204088 -0.3861292843192824 -0.6069291979180885 -0.8871022670271544 -0.8282564445466546 -0.9687233718327408 -0.7552982503965977 -0.8766289377698142 -1.325552208234219 neutral 0.7116674619421797 -1.0110187699275124 -0.26976476122176885 -1.9968335488345148 -0.9378178433324462 0.6928744022487782 0.43993612943219057 -0.6874887467284213 -0.16793769834524086 0.22021501809388128 0.321516176974768 -0.9196273573761302 -0.30212348865751304 0.6813967263597923 0.6253214318832436 1.3834478764156526 -0.08854844871502898 0.010422275480616354 0.3355473666615303 1.1802356655178745 1.112723049246717 -0.06078116250898839 0.42358996226484996 0.777515450619032 -0.30703796156564017 -0.15640213338658387 2.1114287640738536 0.2427491689017222 0.47336273775101817 -7316-41 BS_12ZB7R6A, BS_15ETQ0E4 PT_CW0BJE0Y 883 3.84657534246575 Male Cerebellum/Posterior Fossa infratentorial No loss -0.5415019988009669 -0.042028985385294676 -0.654419178592843 -0.8877267567206053 -0.6984285674889333 -0.9905903301133628 -0.7403017032125075 -1.0270723998153466 -0.4785433176237134 neutral 0.26105014232174323 -0.5687447359344944 -0.18214256629559475 -1.0079726614944573 -0.9749671063108573 0.4696105878410842 0.0026937392589765226 -1.5098020159783074 0.7531633682765503 0.19329339294986986 0.6208564577930034 -0.9345989497865101 -1.1111069979149983 0.3475732199446865 0.6189516742927179 0.03370652333867842 -0.9951310635104076 -0.42449690018602065 1.523890725586452 0.9220206022452966 0.23550515610272602 -0.07602823748676776 0.15231664581547502 1.6111860677063254 1.7965659814519805 1.1727961991292204 -0.15710790425990645 -0.5318826242165537 0.40906201903917466 -7316-479 BS_90B22NGP, BS_YZ0P5E8H PT_JCECCFPB 398 0.0657534246575342 Male Cerebellum/Posterior Fossa infratentorial No neutral -0.5415019988009669 -1.2697778764671541 -0.43282036545413416 -1.1055653458377555 -0.6307796597879837 -0.646253608969525 -0.7111711546846468 0.03728316413970544 0.39446434338201325 neutral -2.063644747669401 -0.7848167630526827 -1.495041364682814 -0.7243122708374645 -0.8276221435187828 2.402693279601588 -2.4184987457866662 1.8505243202092447 0.4706506787178733 -0.11807806297698736 2.311127606513621 2.089648315234708 -1.3548646220676834 -2.446167159746696 -3.035075727649967 -1.193532675395477 -0.7889643440895275 -1.8079176402240127 -1.0135083905050395 -2.218730776988553 -1.8135400439869849 -1.8401473874723437 -3.4716552616871836 -0.490469526829918 2.4752073725509045 -0.6873474566722915 -1.1139775516861594 -0.5979814635908083 0.10021335416260717 -7316-525 BS_1QNTEZPS, BS_9KDA3HG6 PT_5CKDR2SF 394 36.986301369863 Female Brain Stem- Pons;Cerebellum/Posterior Fossa infratentorial Yes loss 2.200139435542012 1.7926608596027542 2.3509901992594187 0.7018152635981585 1.6667427564394819 1.802327281473591 -0.7552982503965977 -1.0270723998153466 -0.6578662702091085 neutral 0.7633415772797665 -0.26205751856284665 -0.9836877245882221 0.25937944543913777 -0.01321734010330177 -0.48733954261471074 0.46462214983570677 -0.4951645003277648 -1.0534917372859318 0.03365357509654191 -0.39383558228831794 -0.4858431698325982 -0.12988283918426352 0.5495277523377926 0.011519996455646705 -0.808701124312061 0.4749232214598581 0.1107863928397404 -0.1808832868700253 -0.046927443120010924 -0.1276918055136466 -0.6124739599576545 0.6337381217872986 -0.2572775450067346 -0.5024564042657679 -0.3110218538819274 -0.36420936220874534 -0.5979814635908083 0.11663055894009913 -7316-820 BS_N0877CX1, BS_P7CY04E7 PT_RRG1V7EP 230 48.4931506849315 Female Parietal Lobe;Temporal Lobe supratentorial No loss -0.5415019988009669 1.3139182983649407 -0.43282036545413416 0.4307600797049104 -0.6176003357022976 -0.8450751738811656 -0.5923942121590768 -0.9878454391863956 -1.0470331950525609 loss -1.2903240762649815 -0.3951522803743727 0.6124090150527383 -0.15279808350140936 -0.9499619940813293 -0.030911105615354477 0.5386601611145514 0.23160611258045719 2.144522123526306 -0.11394498738003 -1.252959680608101 -0.9575561733510554 -0.6450612606560066 0.1646778886705633 0.21979016813068541 0.4036703512349915 2.0150207741696096 -0.8025962044956212 -0.5919796739760744 0.2577608061574126 -0.5285981661786578 0.5538335309053596 0.22594893487624684 -0.33107460621584883 -0.006878984425661182 1.6860827890705776 1.1811623990040723 2.6118572305440915 0.24146972026894423 -7316-878 BS_J483EMFP, BS_SWHQ8FDW PT_ESHACWF6 1506 19.0684931506849 Female Temporal Lobe supratentorial No loss -0.5415019988009669 -0.8194303120875734 -0.0043455862494381535 0.6493175673605023 -0.5915762918634206 -0.2804458033540643 0.7343976789631367 1.1150480058269063 0.8246138264422769 gain 0.8360384726372354 1.0411018409624015 0.9259920379604423 0.7946131147567616 1.8254473636821948 -0.6283715277242843 0.7984522208719828 0.35306987822365865 -0.05660199410601024 -0.48307930594748744 0.1527745929125915 2.0968201962606794 0.46089319209967855 0.3427697399276419 0.7554245782328265 0.8597094804922618 -0.4452106475304891 0.13937773602458559 0.988771979933614 0.054214731622210896 1.2668793037111885 -1.1626639642912635 -1.242847796160684 -0.9109932979855095 -0.4855682150184407 -0.1438676409013662 -0.4642298069934527 0.2427491689017222 1.359891795735584 -7316-918 BS_31TF0P1N, BS_CKY2TTXG PT_M04EC74B 345 16.2739726027397 Male Skull supratentorial No loss -0.5415019988009669 -0.24046579865307624 -0.6912279141376907 0.43503582194826357 -0.858661038657048 -0.9687233718327408 -0.7403017032125075 -1.0203768835341809 -2.054577733356333 neutral 0.015128050535611113 -1.0422102539171334 -1.3677205249938837 0.8750859101030404 -0.9623419682608354 1.2846271205331192 -0.25917157648239686 -0.5491979347897403 -1.1863642510680261 -1.2153404144860422 -1.3932731115266273 0.4598915777122082 -1.1050459336315248 0.36583566388166006 0.6733562163418357 1.9384071224767307 -2.0348646678214015 -1.0626712519756945 -0.2589484458766318 1.3054388662438072 -1.0891047846244806 -0.48311744977197935 -1.1117615343197462 -1.0807795475032418 1.111822081874858 -0.21753080981672082 -0.41244300118846294 -0.5979814635908083 1.1016628455896167 +sample_id Kids_First_Biospecimen_ID Kids_First_Participant_ID age_at_diagnosis_days OS_months germline_sex_estimate primary_site location_summary chr_22q_loss SMARCB1_focal_status STAT3 VEGFA OTX2 PRRX1 MITF SPEF1 MSX2 DNAH11 DCT TYR SMARCA4_focal_status HALLMARK_NOTCH_SIGNALING HES6 CDK6 TEAD1 LHX2 MYCN DLL3 ASCL1 HES5 DLL1 GLI2 HALLMARK_MYC_TARGETS_V1 HALLMARK_MYC_TARGETS_V2 MYC TEAD3 HOTAIR tmb +7316-1073 BS_PGHK1JRW, BS_W23ERYW3 PT_TV5DYHNC 1113 Male Thalamus supratentorial No loss 0.9931858798407095 -0.6734435096585513 -0.3195301540087591 0.7167762233395417 -0.013825621239973412 -0.6296701265532815 0.37468939260540163 -0.7984422683741907 -0.3443657853337286 -0.5347967888204088 neutral -0.9633496302285777 -0.4292513084377833 -0.01265847013662434 -1.2148450922996699 -1.1129879454723954 -0.5521577769470015 -0.26506234428421316 -0.2896007762851814 -0.7677136715718141 -0.09078799060843123 0.27575506920874937 -0.09182518847374531 0.2601445942606957 0.7374646450034709 -0.1165195860785807 0.5126213869336954 0.22402644019285903 +7316-1137 BS_GAGRGSSX PT_4J24F353 575 36.1315068493151 Frontal Lobe supratentorial NA NA 1.0598252457216333 0.05477176202762979 -0.25550932440789287 -0.6437044720667396 -0.30427262549641976 -0.7237637477441374 -0.5464844346097164 -0.578727833381572 -0.5169215190120005 -0.5415019988009669 NA -0.9060984813166558 -0.7534850405042054 -1.4270609955326057 1.493676953921475 -0.6666315888089027 -0.9476455291041406 -1.070707133640094 -0.8327022392213496 -0.7677136715718141 0.09915080815548534 0.18424291701098022 0.1546383371561313 0.43902526972708966 0.8133184879230186 0.11947264314153583 -0.5190412250372987 NA +7316-122 BS_DHA5FMVW, BS_QMHND3QK PT_ND34A6PR 2982 87.3205479452055 Female Parietal Lobe supratentorial No loss 0.2235491349730805 -1.4897936634740059 -0.8423212986263 2.001862791161505 0.7484966127380674 -0.4823260271446828 1.9929723858957624 -0.553349043525155 1.7766358127743929 -0.5415019988009669 loss -1.333942072506645 -0.8537958452397699 0.8057045259505096 0.9926572504818238 1.1288518493113238 -0.9429888031702961 1.446364087847446 -0.9259006994000688 -0.9141341458662853 -1.189599279037505 -0.6736721764907859 0.423251349953539 0.5260135450971443 0.8253420065513858 1.0120615197115503 0.9260253112229148 1.8346226338847265 +7316-1771 BS_859AV1DB, BS_MVW01FPB PT_3KM9W8S8 190 17.1945205479452 Female Other locations NOS;Spinal Cord- Lumbar/Thecal Sac;Spinal Cord- Thoracic;Temporal Lobe "NA" No loss 0.3289987999797695 0.09004306683371797 -0.8132351564479341 -0.8282821793331117 -0.9248221624600625 -0.4182248611089406 -1.1440905133099963 -0.39788590070967844 -0.5611356553218738 -0.5415019988009669 loss 0.7296301557014009 0.13005883476786062 -1.4685603986338047 -0.5830384256823989 -0.4170354330550139 1.099354333031074 -0.18118798743841355 0.039547427050308066 0.6384775263413449 -0.8954556770643659 -0.15299500640483402 0.5476297311539426 0.2851967211009413 -0.11549853188374676 0.489334111024365 -0.5979814635908083 0.2130816370078644 +7316-1778 BS_B1HVNV0T, BS_WCNPE0AC PT_FYECBRPP 562 29.4575342465753 Male Brain Stem- Midbrain/Tectum;Ventricles infratentorial No loss -1.1715759506324344 -0.917531433916074 0.28824245559995654 -0.7225400389888915 -0.8331797433220036 0.8453624497486465 -0.4323843140504138 -0.09911341823268521 0.03156944821735099 -0.5415019988009669 neutral -0.4946163699224732 -0.7278795224228612 -1.530067435790284 -1.3572934396721617 -0.20376154320429704 -0.18006026721835652 -0.08671020772933116 -0.07695117990721823 0.8683139124907046 0.28626572053266724 -0.9591934910764467 -2.1622989466071187 -2.8686800229387686 -1.4274899865310795 -2.226700776634571 -0.5979814635908083 0.17203862506413448 +7316-1781 BS_0EN5R1AP, BS_WVW3W6ZB PT_M1RYN7B0 1038 14.2356164383562 Male Frontal Lobe supratentorial No NA -1.0998878825340002 -0.6805114246123781 -0.8039045879524401 1.4522000973970097 1.0571301099300077 0.32936356006209255 -0.26831471444686944 -0.7691960159473054 -0.4741814649464887 1.3716622497068833 NA 0.1537870014826108 0.42680567498456257 0.6841102521077866 0.44369910704876997 1.8505032694239036 0.8145296192415123 0.5657401077635253 1.3282017140255198 0.595329629905017 -0.009511851683037666 0.5638666152998215 0.564920096407464 0.3864788924705036 -0.590040642989226 0.6003888046989315 -0.5979814635908083 0.2924314600990755 +7316-1790 BS_A94A7EJ4, BS_MV6ASWV9 PT_ESHACWF6 1506 19.0684931506849 Female Cerebellum/Posterior Fossa infratentorial No loss -0.5907381079171508 0.7127821695631376 0.547875215571998 0.07132241677122257 -0.6353069633158734 -0.03365631109533356 -1.0668658745186208 -0.12745973403649913 -0.28861426731137907 -0.5347967888204088 neutral 1.0430458840030574 2.0117519387982234 -1.2667497394979899 0.9614317348274674 0.11226914063697721 1.0436230683914787 1.4325674162657587 1.4006508400121969 0.7260780524082507 0.5029466902273972 -0.012324792435626446 0.7528333788436654 0.7294395284184184 -2.4149458871822578 -1.9303666233131076 0.08044759853277893 4.654619579518502 +7316-2090 BS_19EJ85F8 PT_T5KEXCK7 1026 7.52876712328767 Female Brain Stem- Pons;Cerebellum/Posterior Fossa infratentorial No neutral NA NA NA NA NA NA NA NA NA NA neutral NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA 0.37417545888700426 +7316-2110 BS_4E1G7E3G, BS_6GN1FGTB PT_RJ1TJ2KH 218 13.413698630137 Male Cerebellum/Posterior Fossa infratentorial No loss 0.051857722072143765 1.3589522097278677 1.8248938413275149 0.8522094497905341 1.7236518902599738 1.074764559372531 1.179423156629632 1.837672570575437 0.19120536836753946 1.895050517456976 loss -1.4896758876343636 1.2705094755366442 -0.016114426634444748 1.771785137611317 0.5180430566097279 1.5863383072812351 0.7797225368620523 0.76625184279659 0.5086060264476423 1.2971527750984455 0.8117646387142791 -1.4826860895485046 -0.6735743338555666 0.21607486631785178 0.7180873725592115 -0.5979814635908083 0.12176093543306536 +7316-2141 BS_8WJR4AA3, BS_MMNRZ1EQ PT_WG2Z95B5 383 33.6 Male Parietal Lobe;Temporal Lobe supratentorial No neutral -1.855263413263438 -0.45738212506357195 0.4224263711059136 -1.3148297321113558 -0.699265956261734 -0.9687233718327408 -0.5742942532241799 -0.5283829352539844 -0.3927520141336199 -0.33927110435099267 neutral -1.3186544476459143 -0.01199570567482935 0.06287292232117529 -1.551689521608774 0.10824765761010294 -1.1568726445919153 0.22399222746970454 -0.8587282462045184 -0.4011458142005364 -0.9314623848001026 -0.17866547198452995 0.6285871708353128 0.7687438429413467 0.9901191046485864 0.7570753489775809 0.8767559736137422 0.2715679290276795 +7316-2181 BS_KXCY5BN5, BS_NDSWS9TS PT_GH693TT8 738 32.4493150684931 Male Cerebellum/Posterior Fossa;Spinal Cord- Cervical;Spinal Cord- Lumbar/Thecal Sac;Spinal Cord- Thoracic infratentorial Yes loss 0.6947945831606648 0.1214003877834167 1.8278913021265366 1.2499435172846483 1.6285162451019226 1.767326331847199 1.0045245985913691 0.9127574765456168 1.0609766821813307 1.2927352144239614 loss 0.4992975105938683 0.5554496878700897 0.8460148151084552 0.5121232834351451 -0.08380999473377794 0.37793947700911384 0.6574027630769731 0.9253222435773343 0.058324703632510556 0.6565339933914269 -0.9672865079914718 0.4734960163695011 0.16853718708892498 -0.5836917955116351 0.0947491555678798 -0.5063204041563798 0.16143584697867094 +7316-2186 BS_6G6C7VPX, BS_NXZSD2KK PT_XTVQB9S4 291 11.441095890411 Female Frontal Lobe;Meninges/Dura;Parietal Lobe;Spinal Cord- Cervical;Spinal Cord- Lumbar/Thecal Sac;Spinal Cord- Thoracic;Temporal Lobe;Ventricles "NA" No loss 0.74082000929473 1.456306632805449 1.8954467596221884 0.8512313439220148 1.843356976652882 1.8563446672552735 2.3305459070794914 1.8821037408764822 3.6099441036529463 2.5628523499657923 neutral 0.17598874044261412 -0.11753605702749638 0.6917692263199998 1.0045703153946388 0.6814467840286247 0.0019379156208071849 -0.5630907328249674 0.24997082137385132 -0.1211099441035633 -1.0073939028720817 -1.2669634980502094 0.6675596497893819 0.6584406351104305 0.03960933987205409 0.8831700867289152 -0.5979814635908083 0.1819573529505359 +7316-2187 BS_53TV75NN, BS_850BAHH9 PT_HVZTF42R 170 11.9013698630137 Female Frontal Lobe;Parietal Lobe;Temporal Lobe supratentorial No NA 1.3524238861069495 -0.5369217313540176 -0.8132351564479341 0.5162564458754167 -0.5843815265178426 -0.9796084721152905 -0.33294509597551586 -0.858661038657048 -0.654419178592843 -0.5415019988009669 NA 1.9294000426353726 -0.5947041755206769 0.3722056472928659 -0.14110006695990507 0.06519285815064366 -0.8076460657641753 0.07473293650750046 -0.2917804318694729 0.738922889184582 -1.0681661634058541 0.6263437821054239 0.5508413105802699 0.36851448288474264 0.5004087119187005 -0.14123077301172698 -0.5979814635908083 0.19598038203131027 +7316-2224 BS_P7EY9DXG, BS_SCQNN2A2 PT_H8Z52K09 624 4.10958904109589 Male Frontal Lobe;Parietal Lobe supratentorial No loss 0.41623496448236885 0.09953200853482401 -0.8423212986263 -0.8920612357806953 -0.6900998227442469 0.021040588321809554 -0.6179742905357828 -0.4440662789335005 -0.4847336470721381 -0.5415019988009669 neutral 1.330400381485183 1.7546993168437877 1.274825994339568 1.236675768150908 2.719651684755174 1.8719077786024385 1.440355338444996 2.016287730116499 -0.14893849000879877 1.5416989957309806 1.4588207754625968 0.7048320060220163 0.11523922530390879 -1.2571928179138336 -0.18441054844532734 -0.5845011785378568 0.24728414696097265 +7316-2269 BS_9FHSNVS0, BS_ZAT0XJE5 PT_JV9G8MFD 362 28.0767123287671 Female Frontal Lobe supratentorial No neutral 0.7670140515604287 1.6325550902360912 -0.7769158055007344 -1.4649742476428822 -0.005839787071674717 0.24710031539898739 1.26644980821547 1.125027229078876 0.13364584683675595 -0.5281576410959825 neutral -0.3289372312652283 1.6494214300874983 1.5204974704602836 0.778417142983663 0.4438517530223664 1.6805096628569318 2.168015493688739 1.5328870626811761 2.280986782712156 2.28230833706294 2.7599489066245018 -1.6034270949880065 -1.0513984944130588 -0.8097865955493722 0.3386064051306734 -0.5979814635908083 0.16690824857116826 +7316-2276 BS_0FQKT8EY, BS_996ZS2A4 PT_RX1EWBP9 1351 21.0082191780822 Female Frontal Lobe supratentorial No neutral 1.7267704644134256 -0.41813769276491247 -0.8179666694144649 -0.579419274767866 -0.6002901222780674 -0.7690234201866005 0.6472945290823235 -0.553349043525155 -0.654419178592843 -0.5415019988009669 neutral -0.12482764574120155 -0.05005367046969586 -0.6859502715667178 -1.2148450922996699 -0.13882016724395338 -0.6148902994516384 -0.09570312324382474 -0.5524712920419003 -0.8598545308285599 -0.4480139004765075 -0.3352021447765901 0.568889342609881 0.5845753666690464 0.2678463537801695 0.034611819612561844 0.6912841524758266 2.5901560787488878 +7316-2582 BS_1C4WCNQF, BS_GJNCYABP PT_7MZRW1DH 5688 23.2109589041096 Female Frontal Lobe supratentorial No loss 0.13468207869853122 -2.030705146562924 -0.6637806313201037 -0.08998427727463224 0.26230259145211443 -0.4750372101917142 -0.6485246703709447 -0.7691960159473054 -0.5953265586334711 -0.5415019988009669 neutral 0.5538542849412608 -0.9916204848193896 -0.27493728169811193 -1.0709644007626582 0.17477386027868516 -1.1324707986484117 -0.41983669820275765 -0.9623419682608354 -0.7413316698680641 -0.42795436806964043 -0.9471849703645285 0.33438019851068507 0.12351021671140916 0.3133138809857567 0.5311903010872514 -0.43240621268392443 1.019918846801688 +7316-2688 BS_JDMM2XG4, BS_WV0S8N4M PT_32J909WM 860 28.7342465753425 Male Cerebellum/Posterior Fossa;Ventricles infratentorial No loss 0.8076879635450188 -0.3625945502101911 1.830399109351182 0.42096606558454225 1.7063263229107868 2.5174676381007064 1.6507874990575064 1.6873522179432607 0.6270500894144933 1.2344634201543843 neutral 1.1196303259428073 0.0547200777606503 0.5032299914264298 0.771393629259754 0.24920699786018335 -0.4062850496852571 -0.4623356631176945 0.21149467482405568 0.12171315320369083 -0.28981995661671256 -0.9878337921162526 0.3223027288453448 -0.6313544493479766 -0.5972376276371735 0.050636151872123565 -0.5979814635908083 0.1696444493674169 +7316-2933 BS_74FS6GMW, BS_DE26D072 PT_XTVQB9S4 291 11.441095890411 Female Basal Ganglia;Temporal Lobe supratentorial No loss 0.204818199765087 0.6855158461692943 0.49253583749534263 1.2809500084711831 -0.9942499612046696 0.743975230457378 -0.6446393712671488 2.165896307619269 -0.3829275760921679 -0.5281576410959825 loss 1.2259083455618518 0.3779006007015139 1.3611704697947857 0.1052296543028827 0.33642589742291734 0.7154810316463506 0.8013170081988388 0.18103273589626126 0.6028899715368617 0.8169850707834158 0.556046783689436 0.7708866172696625 0.8081389595749565 0.9585763738762982 -0.8113949774464264 -0.5579364554478906 1.6095701183932742 +7316-3045 BS_983Z6CA6 PT_3KM9W8S8 190 17.1945205479452 Female Other locations NOS;Spinal Cord- Lumbar/Thecal Sac;Spinal Cord- Thoracic;Ventricles infratentorial NA NA -0.5475232540332745 1.5878736215769753 -0.8324364037211752 -0.16811628024129216 -0.8643832517894658 0.9619784930226518 -0.10157853949539944 0.9557414235673398 -0.4953734001749602 -0.5215832665770787 NA -1.2028822094968903 0.23466870003068097 -1.4411932996350094 -0.9753916280863769 -1.410078043498128 0.49723354607002684 -1.3107195630053037 -0.5459322743356074 -0.8904289751239572 -0.21533989104144055 -0.7285553260610074 -2.3302337252826013 -1.5631220281357026 0.2629706559775337 -0.12706797108559562 -0.4937179182076291 NA +7316-3680 BS_6VKKMM6M, BS_WWKNJSJ5 PT_RJ1TJ2KH 218 13.413698630137 Male Cerebellum/Posterior Fossa infratentorial No neutral 0.7558914473104463 2.1430549823003644 0.6886968255402246 0.5764696459291551 0.37060992198387444 -0.5044540973125771 0.2959075096378817 0.41348236614193956 0.4456359215680595 1.5760789003486937 neutral -0.407969543233923 -0.5363744164704171 -0.2546428654739587 -0.1754007124305995 -0.2526668960201854 0.5307594906712975 -1.449145145285226 -0.6634735835924094 -0.8089545676553282 0.2804874146221968 0.019041556020645507 -1.2453194838592418 -0.7280478188463401 0.45257156955850814 0.4129716096289956 -0.3852794620626462 1.1810126686808278 +7316-376 BS_74A1TB03, BS_M4923M40 PT_MTE126WM 1923 56.8438356164384 Female Cerebellum/Posterior Fossa;Other locations NOS infratentorial No loss -1.9767371404539456 -0.1477635704749153 -0.7269570573618929 -2.0419877255258085 -1.1527221319582008 -0.7782777772413161 -1.0277761357597557 -0.858661038657048 -0.654419178592843 -0.5415019988009669 neutral -0.3729174266216668 -1.4885226523457935 0.13818962051392478 -0.5219310093100387 -1.399585502878959 -1.2284615315863612 -0.6375032119424716 -0.9142022310443233 -0.8904289751239572 -1.4542568975766914 -0.08625427118578567 0.6217921659876358 0.8560676040601115 1.0736463113632155 0.9030123687661511 1.8518112571996523 0.2773823557197079 +7316-386 BS_GTAJFTTR, BS_K25F4J3V PT_J302B8Y5 826 8.94246575342466 Male Cerebellum/Posterior Fossa infratentorial No loss -1.3653957268028205 -0.7513892477457589 1.1327051403177724 -0.03348779246738776 -0.6145036988386084 -0.581214861580421 0.22982358240861708 -0.386554618071306 -0.5611356553218738 -0.5022364437079205 neutral 1.040734861338501 1.2275767503746577 1.5340247540023426 0.40982008491709954 0.3668492984930109 1.783781786479442 1.1874633335352531 1.9155391686915413 2.9768695954817064 2.183192534671925 1.965537710603289 0.6286261076950425 0.3452389673410694 -1.694250881669251 -0.6959390313205429 -0.5979814635908083 0.3454453505263933 +7316-3890 BS_5WK2KXYW, BS_S71RJ8DH PT_E6FTW238 557 6.54246575342466 Female Cerebellum/Posterior Fossa infratentorial Yes loss -0.772977504626856 -0.8131480447477902 -0.7725562067800743 1.3437448462935768 -0.7719941975861001 -0.12325917097023086 -0.4685830573916802 -0.6984285674889333 -0.3443657853337286 -0.5281576410959825 loss -0.1356131358391518 -0.590916170443317 0.5361575893303322 -0.2020643489529072 0.4938949953021276 -1.0110187699275124 -0.7351720489649514 -0.812620306957091 -0.7949752335954041 0.8901050941111026 0.8347185829674478 0.21447042087966484 0.20893566451769202 0.584860007412991 0.39991870659586476 3.1505617951137332 0.2883271589047025 +7316-3920 BS_E0S2Y0TS PT_6N825561 1564 65.6876712328767 Female Temporal Lobe supratentorial No loss NA NA NA NA NA NA NA NA NA NA neutral NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA 1.8014461992302115 +7316-3937 BS_QX12J6W1, BS_R5G3QP11 PT_XRQHMBHB 2841 20.2191780821918 Male Cranial Nerves NOS supratentorial No neutral 0.07498604298218087 -0.8871022670271544 -0.7725562067800743 -0.5843287297522581 -0.3861292843192824 -0.9687233718327408 -0.7844109617940861 -0.8282564445466546 -0.6069291979180885 -0.5347967888204088 neutral 0.7226859207079509 -1.449936929128119 -1.9968335488345148 -0.08304009800700564 -0.18615922880952165 -1.0110187699275124 -0.8769424657942824 -0.9378178433324462 -0.8019350298897524 -0.8822643528908017 -0.26976476122176885 0.6688235683468003 0.6086078066984014 1.1802356655178745 1.039678292116508 0.2427491689017222 0.47336273775101817 +7316-41 BS_12ZB7R6A, BS_15ETQ0E4 PT_CW0BJE0Y 883 3.84657534246575 Male Cerebellum/Posterior Fossa infratentorial No loss -0.3053110684418508 -0.8877267567206053 -0.7857509189872405 0.08803412337464235 -0.042028985385294676 -0.9905903301133628 -0.7349665441466824 -0.6984285674889333 -0.654419178592843 -0.5415019988009669 neutral 0.2392228614608464 -1.0429702304333206 -1.0079726614944573 -0.5453879183058532 -1.4369215184129873 -0.5687447359344944 -1.3945841469183555 -0.9749671063108573 -0.7812308574823735 0.1658245650452182 -0.18214256629559475 0.357051437458407 0.6352552011672236 0.9220206022452966 0.6397328647577802 -0.5318826242165537 0.40906201903917466 +7316-479 BS_90B22NGP, BS_YZ0P5E8H PT_JCECCFPB 398 0.0657534246575342 Male Cerebellum/Posterior Fossa infratentorial No NA -2.0273602227240044 -1.1055653458377555 -0.41370242213572206 -1.8319305081308852 -1.2697778764671541 -0.646253608969525 -0.7937498163088249 -0.6307796597879837 -0.43282036545413416 -0.5415019988009669 NA -2.0197950476792323 -0.6159037343512936 -0.7243122708374645 -2.442265905096898 -1.6477983131144625 -0.7848167630526827 -1.1869415773680831 -0.8276221435187828 -0.130281305224764 -0.665787775732759 -1.495041364682814 -2.4886056923479667 -3.0862416853209407 -2.218730776988553 -2.5136354768985942 -0.5979814635908083 0.10021335416260717 +7316-525 BS_1QNTEZPS, BS_9KDA3HG6 PT_5CKDR2SF 394 36.986301369863 Female Brain Stem- Pons;Cerebellum/Posterior Fossa infratentorial No loss 0.1542627875318267 0.7018152635981585 1.6978437483191973 0.15548076357988627 1.7926608596027542 1.802327281473591 1.579633753504246 1.6667427564394819 2.3509901992594187 2.200139435542012 neutral 0.7197361248573511 -0.3107125983206954 0.25937944543913777 0.8274463975796303 0.41458807734445796 -0.26205751856284665 -0.8801602214286586 -0.01321734010330177 -0.08541972180646387 -0.375357948373721 -0.9836877245882221 0.5235332944556536 0.03284461478427962 -0.046927443120010924 0.9108875493729702 -0.5979814635908083 0.11663055894009913 +7316-820 BS_N0877CX1, BS_P7CY04E7 PT_RRG1V7EP 230 48.4931506849315 Female Parietal Lobe;Temporal Lobe supratentorial No loss 0.8284811841646288 0.4307600797049104 -0.8324364037211752 0.4498728222868004 1.3139182983649407 -0.8450751738811656 -0.96671185242924 -0.6176003357022976 -0.43282036545413416 -0.5415019988009669 loss -1.3392091812699343 -0.36649793246619616 -0.15279808350140936 -0.030973086461966812 -0.7461627285699566 -0.3951522803743727 -0.08034395079586543 -0.9499619940813293 -0.8673916452750439 -1.0123264346534944 0.6124090150527383 0.18532462635668284 0.22408800887963537 0.2577608061574126 1.389988663992874 2.6118572305440915 0.24146972026894423 +7316-878 BS_J483EMFP, BS_SWHQ8FDW PT_ESHACWF6 1506 19.0684931506849 Female Temporal Lobe supratentorial NA NA -0.4348172142926543 0.6493175673605023 0.27351347907470847 -0.503597409637343 -0.8194303120875734 -0.2804458033540643 -0.5849856716712863 -0.5915762918634206 -0.0043455862494381535 -0.5415019988009669 NA 0.9160341173191595 2.125868831418702 0.7946131147567616 0.5777789371503805 1.4125569999659793 1.0411018409624015 1.5881528343177942 1.8254473636821948 1.5706101517182993 1.0661535905243291 0.9259920379604423 0.35428496916448177 0.7677361184271163 0.054214731622210896 -1.5462710521455274 0.2427491689017222 1.359891795735584 +7316-918 BS_31TF0P1N, BS_CKY2TTXG PT_M04EC74B 345 16.2739726027397 Male Skull supratentorial No loss 0.8313030401188012 0.43503582194826357 -0.8373543832123155 -0.3280766573405245 -0.24046579865307624 -0.9687233718327408 -0.8127720114015597 -0.858661038657048 -0.6912279141376907 -0.5415019988009669 neutral 0.03913175192802231 -0.8872748450990114 0.8750859101030404 0.22352534887194414 -1.3739352763936685 -1.0422102539171334 -0.6696798619940872 -0.9623419682608354 -0.9141341458662853 -1.1053068150543857 -1.3677205249938837 0.3854416964160171 0.7016463796232661 1.3054388662438072 -1.0320369589637237 -0.5979814635908083 1.1016628455896167