confidence_indel_calulation: Wrapper to compute confidence intervals for SNV and INDEL...
In slw287r/yapsa: Yet Another Package for Signature Analysis

Description Usage Arguments Value Examples

Wrapper function around confIntExp, which is applies to every signature or sample pair in a cohort. The extracted lower bound of the confidence intervals are added to the input data which is reodered and melted in order to prepare for visualization with ggplot2. The calculates of confidence intervals is based on a profiling likelihood algorithm and the wrapper calculates the data for the exposure contubution identefied with SNV and INDEL signature decompositions and application of the following cutoffs:

CosmicValid_absCutoffVector
CosmicValid_normCutoffVector
CosmicArtif_absCutoffVector
CosmicArtif_normCutoffVector
PCAWGValidSNV_absCutoffVector
PCAWGValidID_absCutoffVector

The function makes use of differnet YAPSA functions. For each of the above stated cutoff vectors a per PID decompostion of the SNV and INDEL catalog is calulated respectivly using LCD_complex_cutoff_perPID. In a next step, variateExp wich is a wrapper around confIntExp to compute confidence intervals for a cohort is used. A dataframe is returend with the upper and lower bounds of the confidence intervals. In a last step plotExposuresConfidence_indel to plot the exposures to extracted signatures including confidence intervals computed with e.g. by variateExp.

1	confidence_indel_calulation(in_current_indel_df, in_current_snv_df)

`in_current_indel_df`	A INDEL mutational catalog. Mutational catalog can be constucted with `create_indel_mutation_catalogue_from_df`
`in_current_snv_df`	A SNV mutational catalog. Mutational catalog can be constuced with `create_mutation_catalogue_from_df`

A list is returned containing 12 objects. For each cutoff data frame two corrosponding object are present. First, the p gtable object which can be used for gaphically visualization, and second a dataframe containing the corrosponding upper and lower bounds of the confidence intervals.