moonlight: moonlight pipeline

In MoonlightR: Identify oncogenes and tumor suppressor genes from omics data

Description

moonlight is a tool for identification of cancer driver genes. This function wraps the different steps of the complete analysis workflow. Providing different solutions:

1. MoonlighR::FEA

2. MoonlighR::URA

3. MoonlighR::PIA

Usage

moonlight(cancerType = "panCancer", dataType = "Gene expression",
  directory = "GDCdata", BPname = NULL, cor.cut = 0.6,
  qnt.cut = 0.25, Genelist = NULL, fdr.cut = 0.01, logFC.cut = 1,
  corThreshold = 0.6, kNearest = 3, nGenesPerm = 10,
  DiffGenes = FALSE, nBoot = 100, nTF = NULL, nSample = NULL,
  thres.role = 0, stage = NULL, subtype = 0, samples = NULL)

Arguments

cancerType	select cancer type for which analysis should be run. panCancer for all available cancer types in TCGA. Defaults to panCancer
dataType	dataType
directory	directory
BPname	biological processes to use, if NULL: all processes will be used in analysis, RF for candidate; if not NULL the candidates for these processes will be determined (no learning)
cor.cut	cor.cut Threshold
qnt.cut	qnt.cut Threshold
Genelist	Genelist
fdr.cut	fdr.cut Threshold
logFC.cut	logFC.cut Threshold
corThreshold	corThreshold
kNearest	kNearest
nGenesPerm	nGenesPerm
DiffGenes	DiffGenes
nBoot	nBoot
nTF	nTF
nSample	nSample
thres.role	thres.role
stage	stage
subtype	subtype
samples	samples

Value

table with cancer driver genes TSG and OCG.

Examples

dataDEGs <- DPA(dataFilt = dataFilt, dataType = "Gene expression")
# to change with moonlight

MoonlightR documentation built on Nov. 8, 2020, 8:25 p.m.