ActiveDriver: Identification of active protein sites (post-translational...

Description Usage Arguments Value Author(s) References Examples

View source: R/ActiveDriver.R

Description

Identification of active protein sites (post-translational modification sites, signalling domains, etc) with specific and significant mutations.

Usage

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ActiveDriver(sequences, seq_disorder, mutations, active_sites, flank = 7,
  mid_flank = 2, mc.cores = 1, simplified = FALSE,
  return_records = FALSE, skip_mismatch = TRUE,
  regression_type = "poisson", enriched_only = TRUE)

Arguments

sequences

character vector of protein sequences, names are protein IDs.

seq_disorder

character vector of disorder in protein sequences, names are protein IDs and values are strings 1/0 for disordered/ordered protein residues.

mutations

data frame of mutations, with [gene, sample_id, position, wt_residue, mut_residue] as columns.

active_sites

data frame of active sites, with [gene, position, residue, kinase] as columns. Kinase field may be blank and is shown for informative purposes.

flank

numeric for selecting region size around active sites considered important for site activity. Default value is 7. Ignored in case of simplified analysis.

mid_flank

numeric for splitting flanking region size into proximal (<=X) and distal (>X). Default value is 2. Ignored in case of simplified analysis.

mc.cores

numeric for indicating number of computing cores dedicated to computation. Default value is 1.

simplified

true/false for selecting simplified analysis. Default value is FALSE. If TRUE, no flanking regions are considered and only indicated sites are tested for mutations.

return_records

true/false for returning a collection of gene records with more data regarding sites and mutations. Default value is FALSE.

skip_mismatch

true/false for skipping mutations whose reference protein residue does not match expected residue from FASTA sequence file.

regression_type

'nb' for negative binomial, 'poisson' for poisson GLM. The latter is default.

enriched_only

true/false to indicate whether only sites with enriched active site mutations will be included in the final p-value estimation (TRUE is default). If FALSE, sites with less than expected mutations will be also included.

Value

list with the following components: @return all_active_mutations - table with mutations that hit or flank an active site. Additional columns of interest include Status (DI - direct active mutation; N1 - proximal flanking mutation; N2 - distal flanking mutation) and Active_region (region ID of active sites in that protein).

all_active_sites -

all_region_based_pval - p-values for regions of sites, statistics on observed mutations (obs) and expected mutations (exp, low, high based on mean and s.d. from Poisson sampling). The field Region identifies region in all_active_sites.

Author(s)

Juri Reimand <[email protected]>

References

Systematic analysis of somatic mutations in phosphorylation signaling predicts novel cancer drivers (2013, Molecular Systems Biology) by Juri Reimand and Gary Bader.

Examples

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data(ActiveDriver_data)

phos_results = ActiveDriver(sequences, sequence_disorder, mutations, phosphosites)
ovarian_mutations = mutations[grep("ovarian", mutations$sample_id),]
phos_results_ovarian = ActiveDriver(sequences, sequence_disorder, ovarian_mutations, phosphosites)
GBM_muts = mutations[grep("glioblastoma", mutations$sample_id),]
kin_rslt_GBM = ActiveDriver(sequences, sequence_disorder, GBM_muts, kinase_domains, simplified=TRUE)

kin_results = ActiveDriver(sequences, sequence_disorder, mutations, kinase_domains, simplified=TRUE)

reimandlab/ActiveDriver documentation built on Nov. 29, 2017, 2:15 a.m.