driver gene identification algorithm DawnRank 2014
install.packages("devtools")
library(devtools)
install_github("MartinFXP/DawnRank")
library(DawnRank)# load the mutation data
data(brcaExampleMutation)
# load the tumor expression data
data(brcaExampleTumorExpression)
# load the normal expression data
data(brcaExampleNormalExpression)
# load the pathway data
data(brcaExamplePathway)
# load the gold standard
data(goldStandard)
# normalize the tumor and normal data to get the differential expression
normalizedDawn <- DawnNormalize(tumorMat = brcaExampleTumorExpression, normalMat = brcaExampleNormalExpression)
# get the DawnRank Score Get some coffee, this might take a while!
dawnRankScore <- DawnRank(adjMatrix = brcaExamplePathway, mutationMatrix = brcaExampleMutation,
expressionMatrix = normalizedDawn, mu = 3, goldStandard = goldStandard, parallel = 2)
# look at the DawnRank scores for a few patients
dawnRankFrame <- dawnRankScore[[3]]
head(dawnRankFrame)
# get the aggregate DawnRank scores Get some coffee, this might take a
# while!
aggregateDawnRankScore <- condorcetRanking(scoreMatrix = dawnRankScore[[2]],
mutationMatrix = brcaExampleMutation, parallel = 2)
# look at top 10 ranked genes
top10 <- aggregateDawnRankScore[[2]][1:10]
top10
# get the individual cutoff for patient TCGA-A2-A04P
dawnRankFrame$isCGC <- dawnRankFrame$isGoldStandard
library(maxstat)
#NOTE: the latest version of mvnorm should be installed
significance <- patspeccutoff(patient = "TCGA-A2-A04P", ms = dawnRankFrame,
default = 95)
# look for signficance.
significance[[1]]Hou & Ma, 2014
https://genomemedicine.biomedcentral.com/articles/10.1186/s13073-014-0056-8