Moma-class: MOMA Object

Description Fields Methods

Description

Main class encapsulating the input data and logic of the MOMA algorithm

Fields

viper

matrix of inferred activity score inferred by viper

mut

binary mutation matrix 1 for presence of mutation, 0 for not, NA if not determined

cnv

matrix of cnv values. Can be binary or a range.

fusions

binary matrix of fusion events if appliable

pathways

list of pathways/connections to consider as extra evidence in the analysis

gene.blacklist

character vector of genes to not include because of high mutation frequency

output.folder

character vector of location to save files if desired

gene.loc.mapping

data frame of gene names, entrez ids and cytoband locations

nes

field for saving Normalized Enrichment Matrices from the associate events step

interactions

field for saving the MR-interactions list

clustering.results

results from clustering are saved here

ranks

results field for ranking of MRs based on event association analysis

hypotheses

results field for saving events that have enough occurences to be considered

genomic.saturation

results field for genomic saturation analysis

coverage.summaryStats

results field for genomic saturation analysis

checkpoints

results field with the MRs determined to be the checkpoint for each cluster

sample.clustering

field to save sample clustering vector. Numbers are cluster assignments, names are sample ids

Methods

Cluster( clus.eval = c("reliability", "silhouette"), use.parallel = FALSE, cores = 1 )

Cluster the samples after applying the MOMA weights to the VIPER scores

makeInteractions( genomic.event.types = c("amp", "del", "mut", "fus"), cindy.only = FALSE )

Make interaction web for significant MRs based on their associated events

Rank( use.cindy = TRUE, genomic.event.types = c("amp", "del", "mut", "fus"), use.parallel = FALSE, cores = 1 )

Rank MRs based on DIGGIT scores and number of associated events

runDIGGIT(fCNV = NULL, cnvthr = 0.5, min.events = 4, verbose = FALSE)

Run DIGGIT association function to get associations for driver genomic events

saturationCalculation( clustering.solution = NULL, cov.fraction = 0.85, topN = 100, verbose = FALSE )

Calculate the number of MRs it takes to represent the desired coverage fraction of events


MOMA documentation built on Nov. 8, 2020, 6:01 p.m.