hem.fdr: FDR Evaluation

In HEM: Heterogeneous error model for identification of differentially expressed genes under multiple conditions

Description

Computes resampling-based False Discovery Rate (FDR)

Usage

hem.fdr(dat,  n.layer, design, rep=TRUE, hem.out, eb.out=NULL, n.iter=5, q.trim=0.9,
        target.fdr=c(0.001, 0.005, 0.01, 0.05, 0.1, 0.15, 0.20, 0.30, 0.40, 0.50),
        n.digits=10, print.message.on.screen=TRUE)

Arguments

dat	data
n.layer	number of layers: 1=one-layer EM; 2=two-layer EM
design	design matrix
rep	no replication if FALSE
hem.out	output from hem function
eb.out	output from hem.eb.prior function
n.iter	number of iterations
q.trim	quantile used for estimtaing the proportion of true negatives (pi0)
target.fdr	Target FDRs
n.digits	number of digits
print.message.on.screen	if TRUE, process status is shown on screen.

Value

fdr	H-values and corresponding FDRs
pi0	estimated proportion of true negatives
H.null	H-scores from null data
targets	given target FDRs, corrsponding critical values and numbers of significant genes are provided

Author(s)

HyungJun Cho and Jae K. Lee

See Also

hem.eb.prior hem

Examples

data(pbrain)

##construct a design matrix
cond <- c(1,1,1,1,1,1,2,2,2,2,2,2)
ind  <- c(1,1,2,2,3,3,1,1,2,2,3,3)
rep  <- c(1,2,1,2,1,2,1,2,1,2,1,2)
design <- data.frame(cond,ind,rep)

##normalization
pbrain.nor <- hem.preproc(pbrain[,2:13])

##take a subset for a testing purpose;
##use all genes for a practical purpose
pbrain.nor <- pbrain.nor[1:1000,]

##estimate hyperparameters of variances by LPE
#pbrain.eb  <- hem.eb.prior(pbrain.nor, n.layer=2,  design=design,
#                           method.var.e="neb", method.var.b="peb")     

##fit HEM with two layers of error
##using the small numbers of burn-ins and MCMC samples for a testing purpose;
##but increase the numbers for a practical purpose 
#pbrain.hem <- hem(pbrain.nor, n.layer=2,  design=design,burn.ins=10, n.samples=30, 
#              method.var.e="neb", method.var.b="peb", 
#              var.e=pbrain.eb$var.e, var.b=pbrain.eb$var.b)

##Estimate FDR based on resampling 
#pbrain.fdr <- hem.fdr(pbrain.nor, n.layer=2,  design=design, 
#                  hem.out=pbrain.hem, eb.out=pbrain.eb)

HEM documentation built on Nov. 8, 2020, 5:57 p.m.