DominoEffect: Identification of significant mutation hotspot residues.

Description Usage Arguments Value Author(s) Examples

Description

The function identifies individual amino acid residues, which accumulate a high fraction of the overall mutation load within a protein. After detecting mutation hotspots, the function obtains UniProt/Swiss-Prot KB functional and structural annotations for the affected protein regions and checks for the sequence agreement.

Usage

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  DominoEffect(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", write_to_file = "NO")

Arguments

mutation_dataset

Object containing a table with the mutation data (e.g. TCGA point mutations mapped to protein level).

gene_data

DominoData object containing information about Ensembl gene annotations: gene identifiers and regresentative transcript cDNA length.

snp_data

Object containing a table 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"

write_to_file

Option if the identified and annotated hotspots should be written to a file (YES or NO). Default: NO

Value

Results table

Author(s)

Marija Buljan <[email protected]> Peter Blattmann <[email protected]>

Examples

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data("SnpData", package = "DominoEffect")
data("TestData", package = "DominoEffect")
data("DominoData", package = "DominoEffect")

hotspot_mutations <- DominoEffect(mutation_dataset = TestData, 
gene_data = DominoData, snp_data = SnpData)

peterblattmann/DominoEffect documentation built on June 29, 2019, 10:41 a.m.