panGeneGraph: Creates reactome network graph for Genes connected to top...

In sinnweja/panoply: Personalized Cancer Report

Description

Uses Reactome data to create graph that shows the connection between Driver Genes and Connected Genes for the top Drugs in panDrug

Usage

panGeneGraph(panGene, panDrug, minTargets=2, minPathways=2, ndrugs=4, ndrivers=20, ...)

Arguments

panGene	A data.frame of drug test results from panGeneSets
panDrug	A data.frame of drug test results from panDrugSets
minTargets	Retain drug results for drugs that target at least minTargets genes in the cancer and network genes.
minPathways	Filter drug results to those that target genes in at least minPathways, after accounting for minPathPct and minPathSize.
ndrugs	Number of Drugs to use to find Cancer Driver and Network genes in graph
ndrivers	Number of unique Cancer Drive genes in graph
...	Dynamic parameter for the values of additional parameters for the graph plot.

Details

A graph that shows the Cancer Driver Network for the top Drugs in pan Drug. Circles=Druggable, Ellipse=Expressed Druggable Drivers, Red=Cancer Driver Genes, Blue=Network Genes

Value

nothing is returned

Examples

data(clinPanTNBC)
data(genelistPan)
data(cnaPanTNBC)
data(gcPanTNBC)
data(gcinfoPan)
data(variantPanTNBC)
data(dgidbPan)
data(dgiSets)
data(reactome)
patient <- "TCGA-B6-A0IK"
match.index <- which(clinPanTNBC$Vital.Status=="Alive" & clinPanTNBC$PatientID!=patient & clinPanTNBC$age_at_diagnosis>50 & clinPanTNBC$N.stage == "N1" & clinPanTNBC$ndays > 1000)
ptmatch <- clinPanTNBC[match.index,"PatientID"]
drivGenes <- panGeneSets(caseid=patient, controlid=ptmatch, eventOnly=TRUE, variant=variantPanTNBC,
  cna=cnaPanTNBC, gcount=gcPanTNBC, tumorpct=0.3, tailEnd="upper", tailPct=0.1)
set.seed(1000)
drugResults <- panDrugSets(drivGenes, caseids=patient, controlids=ptmatch, gcount=gcPanTNBC,nsim=200, tailEnd="upper") 

panGeneGraph(drivGenes,drugResults)

sinnweja/panoply documentation built on Aug. 9, 2019, 9:56 a.m.