variateExp {YAPSA} | R Documentation |
Wrapper function around confIntExp, which is applied to every signature/sample pair in a cohort. The extracted upper and lower bounds of the confidence intervals are added to the input data which is reordered and melted in order to prepare for visualization with ggplot2.
variateExp( in_catalogue_df, in_sig_df, in_exposures_df, in_sigLevel = 0.05, in_delta = 0.4, in_pdf = NULL )
in_catalogue_df |
Input numerical data frame of the mutational catalog of the cohort to be analyzed. |
in_sig_df |
Numerical data frame of the signatures used for analysis. |
in_exposures_df |
Input numerical data frame of the exposures computed for the cohort to be analyzed. |
in_sigLevel |
Significance level, parameter passed to confIntExp. |
in_delta |
Inflation parameter for the alternative model, parameter passed on to confIntExp |
in_pdf |
Probability distribution function, parameter passed on to confIntExp, if NULL assumed to be normal distribution. |
A melted data frame.
library(BSgenome.Hsapiens.UCSC.hg19) data(lymphoma_test) data(lymphoma_cohort_LCD_results) data(sigs) word_length <- 3 temp_list <- create_mutation_catalogue_from_df( lymphoma_test_df,this_seqnames.field = "CHROM", this_start.field = "POS",this_end.field = "POS", this_PID.field = "PID",this_subgroup.field = "SUBGROUP", this_refGenome = BSgenome.Hsapiens.UCSC.hg19, this_wordLength = word_length) lymphoma_catalogue_df <- temp_list$matrix lymphoma_PIDs <- colnames(lymphoma_catalogue_df) data("lymphoma_cohort_LCD_results") lymphoma_exposures_df <- lymphoma_Nature2013_COSMIC_cutoff_exposures_df[,lymphoma_PIDs] lymphoma_sigs <- rownames(lymphoma_exposures_df) lymphoma_sig_df <- AlexCosmicValid_sig_df[,lymphoma_sigs] lymphoma_complete_df <- variateExp(in_catalogue_df = lymphoma_catalogue_df, in_sig_df = lymphoma_sig_df, in_exposures_df = lymphoma_exposures_df, in_sigLevel = 0.025, in_delta = 0.4) head(lymphoma_complete_df) lymphoma_complete_df$sample <- factor(lymphoma_complete_df$sample, levels = colnames(lymphoma_exposures_df)[ order(colSums(lymphoma_exposures_df), decreasing = TRUE)]) sig_colour_vector <- c("black", AlexCosmicValid_sigInd_df$colour) names(sig_colour_vector) <- c("total", as.character(AlexCosmicValid_sigInd_df$sig)) ggplot(data = lymphoma_complete_df, aes(x = sample, y = exposure, fill = sig)) + geom_bar(stat = "identity") + geom_errorbar(aes(ymin = lower, ymax = upper), width = 0.2) + facet_wrap(~sig, nrow = nrow(lymphoma_exposures_df) + 1) + theme_grey() + theme(panel.border = element_rect(fill = NA, colour = "black"), strip.background = element_rect(colour = "black"), legend.position = "none") + scale_fill_manual(values = sig_colour_vector)