R/abemus.R

In abemus: Adaptive Base Error Model in Ultra-Deep Sequencing Data

#' ABEMUS:  Adaptive per Base Error Model in Ultra-deep Sequencing Data
#'
#' The package abemus is a NGS-based computational method that uses control samples to build global and local sequencing error reference models that are then used to improve the detection of somatic SNVs in cfDNA samples.
#'
#' In step_1 and step_2 only control samples are used to build the per-base error model ( \code{\link{compute_pbem}} )
#' and compute both coverage-dependent and coverage-independent allelic fraction thresholds ( \code{\link{compute_afthreshold}} ).\cr
#' In step_3 tumor samples are inspected and somatic snvs are called ( \code{\link{callsnvs}} ) based on both custom filtering criteria (i.e. minimum coverage, minimum number of reads supporting an alternative allele)
#' and allelic fraction thresholds.\cr
#' Then in step_4, the per-base error model computed in step 1 is exploited to further refine the final set of putative somatic snvs ( \code{\link{apply_scaling_factor}} ).
#
#' @docType package
#' @name abemus
#' @import utils
#' @import stats
#' @import parallel
NULL

globalVariables(c("fread",
                  "afz",
                  "bgpbem",
                  "bombanel_afs",
                  "bombanel_covs",
                  "bombanel_tab_cov_pbem",
                  "datacount_bin",
                  "tab_optimal_R",
                  "th_results_bin"))