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

In reimandlab/ActiveDriver: Finding Cancer Driver Proteins with Enriched Mutations in Post-Translational Modification Sites

Description

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

Usage

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 <[e-mail]>

References

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

Examples

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 May 10, 2019, 12:11 a.m.