identify_hotspots: Identify hotspots

In DominoEffect: Identification and Annotation of Protein Hotspot Residues

Description

The function identify protein hotspot mutation residues

Usage

  identify_hotspots(mutation_dataset, gene_data,
  snp_data, min_n_muts = 5, MAF_thresh = 0.01, flanking_region = c(200, 300), 
  poisson.thr = 0.01, percentage.thr = 0.15, ratio.thr = 45, approach = "percentage")

Arguments

mutation_dataset	Object containing a table with the mutation data (e.g. TCGA point mutations mapped to protein level).
gene_data	Data frame or Txdb object containing information about Ensembl gene annotations: gene identifiers and regresentative transcript cDNA length.
snp_data	Object containing a table or vcf object with information on population SNPs.
min_n_muts	Numeric vector defining a minimum number of mutations that need to occur at the same residue. Default: 5
MAF_thresh	Numeric vector that defines Minor allele frequency threshold for considering reported mutations as population SNPs.
flanking_region	Numeric vector that defines size of a window around the mutation that will be considered. Up to two window sizes are allowed.
poisson.thr	Numeric vector that defines a treshold for the adjusted p-value. Residues with an associated p-value that is lower than the defined value are reported. Default: 0.01
percentage.thr	Number defining the fraction of mutations within the window that need to fall on a single residue in order for it to be classified as a hotspot. Default: 0.15
ratio.thr	Number defining a requirement that a number of mutations on a single residue should exceed what would be expected by chance given a background mutation rate in the window (i.e. the surrounding region). Default: 45
approach	Option to define selection criteria to use precentage.thr or ratio.thr as criterion for finding single residue mutation clusters. Options: "both", "percentage" or "ratio". Default = "percentage"

Value

An object containing information on the significant hotspots, associated Gene and protein identifiers, number of mutations, percentage of mutations within defined windows that map to the same residue and associated p-values.

Author(s)

Marija Buljan <[e-mail]> Peter Blattmann <[e-mail]>

Examples

data("SnpData", package = "DominoEffect")
data("TestData", package = "DominoEffect")
data("DominoData", package = "DominoEffect")
hotspot_mutations <- identify_hotspots(mutation_dataset = TestData, 
   gene_data = DominoData, snp_data = SnpData)

DominoEffect documentation built on Nov. 8, 2020, 5:46 p.m.