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Fixes #24. Loading method updated to non-LazyData method
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@ytakemon
ytakemon committed Mar 2, 2022
1 parent 6e9ddfb commit f1cf015
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2 changes: 1 addition & 1 deletion README.Rmd
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Expand Up @@ -191,7 +191,7 @@ screen_results <- GINI_screen(

```{r load_prepared_results, eval = Final_eval, include = FALSE}
# Load prepared ARID1A screen result
data("sample_ARID1A_KO_screen")
load("data/sample_ARID1A_KO_screen.rda", envir = environment())
screen_results <- sample_ARID1A_KO_screen
```

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115 changes: 111 additions & 4 deletions README.md
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Expand Up @@ -77,6 +77,14 @@ For this example you will need to call the following libraries
``` r
library(GINIR)
library(tidyverse)
#> ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ──
#> ✓ ggplot2 3.3.5 ✓ purrr 0.3.4
#> ✓ tibble 3.1.6 ✓ dplyr 1.0.8
#> ✓ tidyr 1.2.0 ✓ stringr 1.4.0
#> ✓ readr 2.1.2 ✓ forcats 0.5.1
#> ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
#> x dplyr::filter() masks stats::filter()
#> x dplyr::lag() masks stats::lag()
```

### Exploring cell lines
Expand All @@ -102,9 +110,39 @@ list_available_mutations(Gene = "TP53", Is_hotspot = TRUE)
``` r
# List all available cancer types
list_available_cancer_types()
#> [1] "Ovarian Cancer" "Leukemia"
#> [3] "Colon/Colorectal Cancer" "Skin Cancer"
#> [5] "Lung Cancer" "Bladder Cancer"
#> [7] "Kidney Cancer" "Breast Cancer"
#> [9] "Pancreatic Cancer" "Myeloma"
#> [11] "Brain Cancer" "Sarcoma"
#> [13] "Lymphoma" "Bone Cancer"
#> [15] "Fibroblast" "Gastric Cancer"
#> [17] "Engineered" "Thyroid Cancer"
#> [19] "Neuroblastoma" "Prostate Cancer"
#> [21] "Rhabdoid" "Gallbladder Cancer"
#> [23] "Endometrial/Uterine Cancer" "Head and Neck Cancer"
#> [25] "Bile Duct Cancer" "Esophageal Cancer"
#> [27] "Liver Cancer" "Cervical Cancer"
#> [29] "Immortalized" "Unknown"
#> [31] "Eye Cancer" "Adrenal Cancer"
#> [33] "Liposarcoma" "Embryonal Cancer"
#> [35] "Teratoma" "Non-Cancerous"
#> [37] NA

# List all available cancer subtypes
list_available_cancer_subtypes(input_disease = "Lung Cancer")
#> [1] "Non-Small Cell Lung Cancer (NSCLC), Adenocarcinoma"
#> [2] "Non-Small Cell Lung Cancer (NSCLC), Large Cell Carcinoma"
#> [3] "Mesothelioma"
#> [4] "Small Cell Lung Cancer (SCLC)"
#> [5] "Non-Small Cell Lung Cancer (NSCLC), unspecified"
#> [6] "Non-Small Cell Lung Cancer (NSCLC), Squamous Cell Carcinoma"
#> [7] "Non-Small Cell Lung Cancer (NSCLC), Adenosquamous Carcinoma"
#> [8] "Carcinoid"
#> [9] "Non-Small Cell Lung Cancer (NSCLC), Bronchoalveolar Carcinoma"
#> [10] "Non-Small Cell Lung Cancer (NSCLC), Mucoepidermoid Carcinoma"
#> [11] "Carcinoma"
```

### Selecting mutant and control cell line groups
Expand Down Expand Up @@ -138,19 +176,38 @@ The cell line groups assigned by default are:

``` r
ARID1A_groups <- select_cell_lines(Input_gene = "ARID1A")
#> Selecting mutant groups for: ARID1A in all cancer cell lines

# Show number of cell lines in each group
count(ARID1A_groups, Group)
#> # A tibble: 6 × 2
#> Group n
#> <chr> <int>
#> 1 Amplified 24
#> 2 ARID1A_HetDel 105
#> 3 ARID1A_HomDel 13
#> 4 ARID1A_T-HetDel 21
#> 5 Control 529
#> 6 Others 47
```

#### Optional filter for specific cancer types

``` r
# Find pancreatic cancer cell lines with ARID1A mutations
ARID1A_pancr_groups <- select_cell_lines(Input_gene = "ARID1A", Input_disease = "Pancreatic Cancer")
#> Selecting mutant groups for: ARID1A in Pancreatic Cancer, cell lines

# Show number of cell lines in each group
count(ARID1A_pancr_groups, Group)
#> # A tibble: 5 × 2
#> Group n
#> <chr> <int>
#> 1 ARID1A_HetDel 7
#> 2 ARID1A_HomDel 4
#> 3 ARID1A_T-HetDel 1
#> 4 Control 18
#> 5 Others 1
```

### Check for differential expression
Expand All @@ -170,6 +227,7 @@ ARID1A_HomDel_muts_and_ctrls <- ARID1A_groups %>% filter(Group %in% c("ARID1A_Ho
ARID1A_HomDel_muts_and_ctrls_rna <- extract_rna_expr(
Input_samples = ARID1A_HomDel_muts_and_ctrls$DepMap_ID,
Input_genes = "ARID1A")
#> [1] "Following sample did not contain profile data: ACH-001151, ACH-001685, ACH-001956"
```

Not all cell lines contain RNA and/or protein expression profiles, and
Expand All @@ -194,15 +252,29 @@ lines compared to `Controls`.
# Append groups and test differential expression
ARID1A_HomDel_muts_and_ctrls_rna <- left_join(ARID1A_HomDel_muts_and_ctrls_rna,
ARID1A_HomDel_muts_and_ctrls %>% select(DepMap_ID, Group))
#> Joining, by = "DepMap_ID"

# T-test
t.test(ARID1A_8289 ~ Group, ARID1A_HomDel_muts_and_ctrls_rna)
#>
#> Welch Two Sample t-test
#>
#> data: ARID1A_8289 by Group
#> t = -5.4354, df = 12.591, p-value = 0.0001276
#> alternative hypothesis: true difference in means is not equal to 0
#> 95 percent confidence interval:
#> -1.7621880 -0.7574242
#> sample estimates:
#> mean in group ARID1A_HomDel mean in group Control
#> 3.557090 4.816896

# plot
ggplot(ARID1A_HomDel_muts_and_ctrls_rna, aes(x = Group, y = ARID1A_8289)) +
geom_boxplot()
```

<img src="man/figures/README-Check_expression_rna_stats-1.svg" width="100%" />

### Perform *in silico* genetic screen

After determining cell lines in the `ARID1A_HomDel` group has
Expand Down Expand Up @@ -276,6 +348,15 @@ screen_results %>%
filter(Pval < 0.05) %>%
arrange(-Interaction_score) %>%
select(GeneNames:Mutant_median, Pval, Interaction_score) %>% head
#> # A tibble: 6 × 5
#> GeneNames Control_median Mutant_median Pval Interaction_score
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 ARID1B 0.0364 0.590 0.0000000342 7.47
#> 2 OR2M3 0.00912 0.0279 0.000255 3.59
#> 3 C1QTNF5 0.0794 0.253 0.000334 3.48
#> 4 LSM1 0.0273 0.112 0.000548 3.26
#> 5 ONECUT1 0.00116 0.00451 0.00107 2.97
#> 6 ANP32B 0.0160 0.0566 0.00119 2.92
```

We immediately see that *ARID1B*, a known synthetic lethal interaction
Expand All @@ -298,6 +379,8 @@ plot_screen(result_df = screen_results,
label_n = 3)
```

<img src="man/figures/README-plot-1.svg" width="100%" />

## Session Info

``` r
Expand All @@ -321,9 +404,33 @@ sessionInfo()
#> attached base packages:
#> [1] stats graphics grDevices utils datasets methods base
#>
#> other attached packages:
#> [1] forcats_0.5.1 stringr_1.4.0 dplyr_1.0.8 purrr_0.3.4
#> [5] readr_2.1.2 tidyr_1.2.0 tibble_3.1.6 ggplot2_3.3.5
#> [9] tidyverse_1.3.1 GINIR_0.1.0
#>
#> loaded via a namespace (and not attached):
#> [1] compiler_4.0.2 magrittr_2.0.2 cli_3.2.0 tools_4.0.2
#> [5] htmltools_0.5.1.1 rstudioapi_0.13 yaml_2.2.1 stringi_1.7.6
#> [9] rmarkdown_2.9 knitr_1.37 stringr_1.4.0 xfun_0.29
#> [13] digest_0.6.29 rlang_1.0.1 evaluate_0.14
#> [1] matrixStats_0.59.0 fs_1.5.0 doMC_1.3.8 lubridate_1.7.10
#> [5] httr_1.4.2 tools_4.0.2 backports_1.4.1 utf8_1.2.2
#> [9] R6_2.5.1 nortest_1.0-4 DBI_1.1.1 colorspace_2.0-3
#> [13] withr_2.4.3 tidyselect_1.1.2 Exact_2.1 compiler_4.0.2
#> [17] rcompanion_2.4.1 cli_3.2.0 rvest_1.0.0 expm_0.999-6
#> [21] xml2_1.3.3 sandwich_3.0-1 labeling_0.4.2 diptest_0.76-0
#> [25] scales_1.1.1 lmtest_0.9-38 mvtnorm_1.1-2 proxy_0.4-26
#> [29] multcompView_0.1-8 digest_0.6.29 rmarkdown_2.9 pkgconfig_2.0.3
#> [33] htmltools_0.5.1.1 highr_0.9 dbplyr_2.1.1 rlang_1.0.1
#> [37] readxl_1.3.1 rstudioapi_0.13 farver_2.1.0 generics_0.1.2
#> [41] zoo_1.8-9 jsonlite_1.7.2 magrittr_2.0.2 modeltools_0.2-23
#> [45] Matrix_1.3-4 Rcpp_1.0.8 DescTools_0.99.42 munsell_0.5.0
#> [49] fansi_1.0.2 lifecycle_1.0.1 stringi_1.7.6 multcomp_1.4-17
#> [53] yaml_2.2.1 MASS_7.3-51.6 rootSolve_1.8.2.1 plyr_1.8.6
#> [57] grid_4.0.2 parallel_4.0.2 ggrepel_0.9.1 crayon_1.5.0
#> [61] lmom_2.8 lattice_0.20-41 haven_2.4.1 splines_4.0.2
#> [65] hms_1.1.1 knitr_1.37 pillar_1.7.0 boot_1.3-25
#> [69] gld_2.6.2 codetools_0.2-16 stats4_4.0.2 reprex_2.0.0
#> [73] glue_1.6.2 evaluate_0.14 data.table_1.14.0 modelr_0.1.8
#> [77] vctrs_0.3.8 tzdb_0.2.0 foreach_1.5.2 cellranger_1.1.0
#> [81] gtable_0.3.0 assertthat_0.2.1 xfun_0.29 coin_1.4-1
#> [85] libcoin_1.0-8 broom_0.7.12 e1071_1.7-7 class_7.3-17
#> [89] survival_3.1-12 iterators_1.0.14 TH.data_1.0-10 ellipsis_0.3.2
```
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