getEnr: Get ENR for all networks in a specified directory

In BaderLab/netDx: Network-based patient classifier

Description

Get ENR for all networks in a specified directory

Usage

getEnr(
  netDir,
  pheno_DF,
  predClass,
  netGrep = "_cont.txt$",
  enrType = "binary",
  ...
)

Arguments

netDir	(char) directory containing interaction networks
pheno_DF	(data.frame) table with patient ID and status. Must contain columns for Patient ID (named "ID") and class (named "STATUS"). Status should be a char; value of predictor class should be specified in predClass param; all other values are considered non-predictor class Rows with duplicate IDs will be excluded.
predClass	(char) value for patients in predictor class
netGrep	(char) pattern for grep-ing network text files, used in dir(pattern=..) argument
enrType	(char) how enrichment should be computed. Options are: 1) binary: Skew of number of (+,+) interactions relative to other interactions. Used when all edges in network are set to 1 (e.g. shared CNV overlap) 2) corr: 0.5*((mean weight of (+,+) edges)-(mean weight of other edges))
...	arguments for countIntType_batch

Details

For each network, compute the number of (+,+) and other (+,-),(-,+),(-,-) interactions. From this compute network ENR. The measure of (+,+)-enrichment is defined as: ENR(network N) = ((num (+,+) edges) - (num other edges))/(num edges). A network with only (+,+) interactions has an ENR=1 ; a network with no (+,+) interactions has an ENR=-1; a network with a balance of the two has ENR=0.

Value

(list): 1) plusID (char) vector of + nodes 2) minusID (char) vector of - nodes 3) orig_rat (numeric) ENR for data networks 4) fList (char) set of networks processed 5) orig (data.frame) output of countIntType_batch for input networks

Examples

d <- tempdir()
options(stringsAsFactors=FALSE)
pids <- paste("P",seq_len(5),sep="")
pheno <- data.frame(ID=pids,STATUS=c(rep("case",3),rep("control",2)))

# write PSN
m1 <- matrix(c("P1","P1","P2","P2","P3","P4",1,1,1),byrow=FALSE,ncol=3)
write.table(m1,file=paste(d,"net1.nettxt",sep=getFileSep()),sep="\t",
col.names=FALSE,row.names=FALSE,quote=FALSE)
m2 <- matrix(c("P3","P4",1),nrow=1)
write.table(m2,file=paste(d,"net2.nettxt",sep=getFileSep()),sep="\t",
col.names=FALSE,row.names=FALSE,quote=FALSE)

# compute enrichment
x <- countPatientsInNet(d,dir(d,pattern=c("net1.nettxt","net2.nettxt")), pids)
getEnr(d,pheno,"case","nettxt$")

BaderLab/netDx documentation built on Sept. 26, 2021, 9:13 a.m.