hem.fdr {HEM} | R Documentation |
FDR Evaluation
Description
Computes resampling-based False Discovery Rate (FDR)
Usage
hem.fdr(dat, tr=" ", n.layer, design, 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 |
tr |
if "log2", "log10", or "loge", then log-transformation (with base 2, 10, or e respectively) is taken. |
n.layer |
number of layers: 1=one-layer EM; 2=two-layer EM |
design |
design matrix |
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)
[Package
HEM version 1.0.4
Index]