confIntExp: Compute confidence intervals

In YAPSA: Yet Another Package for Signature Analysis

Description

Compute confidence intervals using the (log-)likelihood ratio test, primarily for one input sample.

Usage

confIntExp(
  in_ind = 1,
  in_sigLevel = 0.05,
  in_delta = 1,
  in_exposure_vector = NULL,
  in_verbose = FALSE,
  ...
)

Arguments

in_ind	Index of the input signature to be variated.
in_sigLevel	Significance leve (one-sided)
in_delta	Inflation parameter for the alternative model.
in_exposure_vector	Exposure vector computed for the input sample.
in_verbose	Whether to run verbose (TRUE) or not (FALSE)
...	Input parameters passed on to variateExpSingle.

Value

A list with entries

• upper: Upper bound of the confidence interval

• lower: Lower bound of the confidence interval

Examples

 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]
 confIntExp(in_ind = 1, in_sigLevel = 0.05, in_delta = 0.4,
            in_exposure_vector = lymphoma_exposures_df[, 1],
            in_catalogue_vector = lymphoma_catalogue_df[, 1],
            in_sig_df = lymphoma_sig_df)
            

YAPSA documentation built on Nov. 8, 2020, 4:59 p.m.