Selected Events Linked by Evolutionary Conditions in Cancer

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Documentation for package ‘SelectSim’ version 0.1.6

• DESCRIPTION file
• User guides, package vignettes and other documentation
• Package NEWS
• Package README

Help Pages

add	Sum a list of matrices element-wise
al.pairwise.alteration.stats	Compute pairwise alteration statistics for an alteration landscape
al.stats	Compute alteration landscape statistics
am.pairwise.alteration.coverage	Compute pairwise alteration coverage statistics
am.pairwise.alteration.overlap	Compute pairwise alteration co-occurrence counts
am.stats	Compute summary statistics for a binary alteration matrix
am.weight.pairwise.alteration.overlap	Compute TMB-weighted pairwise alteration overlap
binary.yule	Compute Yule Q coefficient for all gene pairs
effectSize	Compute effect size between observed and expected overlap
estimateFDR2	Estimate FDR by scanning observed vs null effect sizes
estimate_pairwise_p	Compute p-values for all gene pairs in a results table
estimate_p_val	Compute empirical two-sided p-value for a gene pair
filter_maf_column	Filter maf function
filter_maf_complex	Filter a MAF dataframe by a combination of column values
filter_maf_gene.name	Filter a MAF dataframe by gene name
filter_maf_ignore	This function filters a MAF dataframe by retaining (or discarding) ignore mutations
filter_maf_missense	This function filters a MAF dataframe by retaining (or discarding) missense mutations
filter_maf_mutation.type	Filter a MAF dataframe by mutation type
filter_maf_mutations	Filter a MAF dataframe by specific gene-mutation combinations
filter_maf_sample	Filter a MAF dataframe by sample ID
filter_maf_schema	This function filters a MAF dataframe by sample id
filter_maf_truncating	This function filters a MAF dataframe by retaining (or discarding) truncating mutations
generateS	Generate S matrix
generateW_block	Generate block-aware sample weight matrix
generateW_mean_tmb	Generate sample weight matrix from TMB values
GENIE_maf_schema	GENIE_maf_schema: schema for GENIE maf file to process the mutations
get.blocks	Get sample/alteration blocks
interaction.table	Build the full interaction results table from selectX outputs
luad_maf	Lung adenocarcinoma MAF from TCGA cohort
luad_result	Lung adenocarcinoma from TCGA cohort as SelectSim run results
luad_run_data	Lung adenocarcinoma from TCGA cohort as SelectSim run object
maf2gam	Generate gam from the maf file
mutation_type	Mutation list object
new.AL.general	Create an Alteration Landscape (AL) object
new.ALS	Initialize an Alteration Landscape Stats (ALS) container
new.AMS	Initialize an Alteration Matrix Stats (AMS) container
null_model_parallel	Generating the null_simulation matrix
obs_exp_scatter	Scatter plot of observed vs expected weighted co-mutation
oncokb_genes	OncoKB v3.9 cancer genes
oncokb_truncating_genes	OncoKB v3.9 cancer genes consider for truncating mutations
overlap_pair_extract	Extract null-model weighted overlap distribution for a gene pair
r.am.pairwise.alteration.overlap	Compute null overlap matrix
r.effectSize	Compute effect sizes for null model permutations
retrieveOutliers	Identify outlier null-model matrices
ridge_plot_ed	Ridge plot of null-model background distribution for significant gene pairs
ridge_plot_ed_compare	Ridge plot comparing null-model distributions for two datasets
selectX	SelectX main function from SelectSim to create alteration object with background model
stat_maf_column	Summary functions for MAF file
stat_maf_gene	Count mutations per gene in a MAF file
stat_maf_sample	Count mutations per sample in a MAF file
TCGA_maf_schema	TCGA_maf_schema: schema for TCGA maf file to process the mutations
template.obj.gen	Generate the template matrix
theme_Publication	A clean ggplot2 theme for publication-quality plots
variant_catalogue	OncoKB v3.9 cancer genes
w.r.am.pairwise.alteration.overlap	Compute null weighted overlap matrix