This notebook looks at the defining lesions for all samples for the issue of molecular subtyping high-grade glioma samples in the OpenPBTA dataset.
+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-HGG/01-HGG-molecular-subtyping-defining-lesions.Rmd', clean = TRUE)"
# Get `magrittr` pipe
+`%>%` <- dplyr::`%>%`Registered S3 method overwritten by 'dplyr':
+ method from
+ print.rowwise_df # 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
+results_dir <-
+ file.path(root_dir, "analyses", "molecular-subtyping-HGG", "results")
+
+if (!dir.exists(results_dir)) {
+ dir.create(results_dir)
+}
+
+# Read in metadata
+metadata <-
+ readr::read_tsv(file.path(root_dir, "data", "pbta-histologies.tsv"))Parsed with column specification:
+cols(
+ .default = col_character(),
+ OS_days = [32mcol_double()[39m,
+ age_last_update_days = [32mcol_double()[39m,
+ normal_fraction = [32mcol_double()[39m,
+ tumor_fraction = [32mcol_double()[39m,
+ tumor_ploidy = [32mcol_double()[39m
+)
+See spec(...) for full column specifications.# Select wanted columns in metadata for merging and assign to a new object
+select_metadata <- metadata %>%
+ dplyr::select(Kids_First_Participant_ID,
+ sample_id,
+ Kids_First_Biospecimen_ID,
+ disease_type_new)
+
+# Read in snv consensus mutation data
+snv_df <-
+ data.table::fread(file.path(root_dir,
+ "data",
+ "pbta-snv-consensus-mutation.maf.tsv.gz"))Registered S3 method overwritten by 'data.table':
+ method from
+ print.data.table
+Registered S3 method overwritten by 'R.oo':
+ method from
+ throw.default R.methodsS3
+|--------------------------------------------------|
+|==================================================|# Filter the snv consensus mutatation data for the target lesions
+snv_lesions_df <- snv_df %>%
+ dplyr::select(Tumor_Sample_Barcode, Hugo_Symbol, HGVSp_Short) %>%
+ dplyr::mutate(
+ H3F3A.K28M = dplyr::case_when(Hugo_Symbol == "H3F3A" &
+ HGVSp_Short == "p.K28M" ~ "Yes",
+ TRUE ~ "No"),
+ HIST1H3B.K28M = dplyr::case_when(
+ Hugo_Symbol == "HIST1H3B" & HGVSp_Short == "p.K28M" ~ "Yes",
+ TRUE ~ "No"
+ ),
+ H3F3A.G35R = dplyr::case_when(Hugo_Symbol == "H3F3A" &
+ HGVSp_Short == "p.G35R" ~ "Yes",
+ TRUE ~ "No"),
+ H3F3A.G35V = dplyr::case_when(Hugo_Symbol == "H3F3A" &
+ HGVSp_Short == "p.G35V" ~ "Yes",
+ TRUE ~ "No")
+ ) %>%
+ dplyr::select(
+ -HGVSp_Short,
+ -Hugo_Symbol
+ )
+
+# Join the selected variables from the metadata with the snv consensus mutation
+# and defining lesions data.frame
+snv_lesions_df <- select_metadata %>%
+ dplyr::right_join(snv_lesions_df,
+ by = c("Kids_First_Biospecimen_ID" = "Tumor_Sample_Barcode")) %>%
+ dplyr::select(
+ -disease_type_new,
+ dplyr::everything()
+ ) %>%
+ dplyr::distinct() %>%
+ dplyr::mutate(
+ disease_type_reclassified = dplyr::case_when(
+ H3F3A.K28M == "Yes" ~ "High-grade glioma, H3 K28 mutant",
+ HIST1H3B.K28M == "Yes" ~ "High-grade glioma, H3 K28 mutant",
+ H3F3A.G35R == "Yes" ~ "High-grade glioma, H3 G35 mutant",
+ H3F3A.G35V == "Yes" ~ "High-grade glioma, H3 G35 mutant",
+ TRUE ~ as.character(disease_type_new)
+ )
+ )
+
+# Display `snv_lesions_df`
+snv_lesions_df # Save final data.frame to file
+readr::write_tsv(snv_lesions_df,
+ file.path(results_dir, "HGG_defining_lesions.tsv"))# Isolate the samples with the specified mutations that were not classified
+# as HGG or DIPG
+snv_lesions_df %>%
+ dplyr::filter(
+ grepl("High-grade glioma", disease_type_reclassified) &
+ !(disease_type_new %in% c("High-grade glioma",
+ "Brainstem glioma- Diffuse intrinsic pontine glioma"))
+ )# Print the session information
+sessionInfo()R version 3.6.0 (2019-04-26)
+Platform: x86_64-pc-linux-gnu (64-bit)
+Running under: Debian GNU/Linux 9 (stretch)
+
+Matrix products: default
+BLAS/LAPACK: /usr/lib/libopenblasp-r0.2.19.so
+
+locale:
+ [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
+ [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=C LC_PAPER=en_US.UTF-8 LC_NAME=C
+ [9] LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
+
+attached base packages:
+[1] stats graphics grDevices utils datasets methods base
+
+loaded via a namespace (and not attached):
+ [1] Rcpp_1.0.1 rprojroot_1.3-2 crayon_1.3.4 dplyr_0.8.3 assertthat_0.2.1 R.methodsS3_1.7.1
+ [7] R6_2.4.0 backports_1.1.4 magrittr_1.5 pillar_1.4.2 rlang_0.4.0 data.table_1.12.2
+[13] rstudioapi_0.10 R.oo_1.22.0 R.utils_2.9.0 tools_3.6.0 readr_1.3.1 glue_1.3.1
+[19] purrr_0.3.2 hms_0.4.2 xfun_0.8 compiler_3.6.0 pkgconfig_2.0.2 knitr_1.23
+[25] tidyselect_0.2.5 tibble_2.1.3