topGene {RankProd} | R Documentation |
Identify differentially expressed genes using rank product method
topGene(x,cutoff=NULL,num.gene=NULL,logged=TRUE,logbase=2,gene.names=NULL)
x |
the value returned by the
function RP, RP.advance or
Rsum.advance |
cutoff |
threshold in pfp used to select genes |
num.gene |
number of candidate genes of interests, if cutoff is provided, this will be ignored |
logged |
if "TRUE", data has bee logged, otherwise set it to "FALSE" |
logbase |
base used when taking log, used to restore the fold change.The default value is 2, this will be ignored if logged=FALSE |
gene.names |
if "NULL", no gene name will be attached to the output table |
Two tables of identified genes with
gene.index: index of gene in the original data set
RP/Rsum: Computed rank product/sum for each gene
FC:(class1/class2): Expression Fold change of class 1/ class 2.
pfp: estimated pfp for each gene if the gene is used as cutoff point
Table 1 list genes that are up-regulated under class 2, Table 1 ist
genes that are down-regulated under class 2,
Fangxin Hong fhong@salk.edu
# Load the data of Golub et al. (1999). data(golub) # contains a 3051x38 gene expression # matrix called golub, a vector of length called golub.cl # that consists of the 38 class labels, # and a matrix called golub.gnames whose third column # contains the gene names. data(golub) #use a subset of data as example, apply the rank #product method subset <- c(1:4,28:30) #Setting rand=123, to make the results reproducible, #identify genes RP.out <- RP(golub[,subset],golub.cl[subset],rand=123) #get two lists of differentially expressed genes #by setting FDR (false discivery rate) =0.05 table=topGene(RP.out,cutoff=0.05,logged=TRUE,logbase=2, gene.names=golub.gnames[,3]) table$Table1 table$Table2 #by selecting top 10 genes topGene(RP.out,num.gene=10,gene.names=golub.gnames[,3])