lmtstat: A wrapper function used to calculated the limma t-statistics
In iChip: Bayesian Modeling of ChIP-chip Data Through Hidden Ising Models

Description Usage Arguments Value Author(s) References See Also Examples

View source: R/iChip.R

A wrapper function used to calculated the empirical Bayes t-statistics (limma t-statistics) using functions in the limma package.

1	lmtstat(IP,CON)

IP

Data matrix for IP-enriched samples, where the rows and columns correspond to the probes and sample replicates, respectively. The number of replicates must be greater than one. If CON is missing, IP is assumed to be in log-ratio format (e.g. log2(IP-enriched/control)). In this case, paired t-statistics are calculated. If CON is NOT missing, IP and CON are assumed to be the normalized intensities for the IP-enriched and control samples, respectively. In this case, two-sample t-statistics are calculated.

CON

Data matrix for control samples, where the rows and columns correspond to the probes and sample replicates, respectively. The number of replicates must be greater than one.

Empirical Bayes t-statistics calculated using functions in the limma package.

Qianxing Mo qianxing.mo@moffitt.org

Smyth, G. K. (2004). Linear models and empirical Bayes methods for assessing differential expression in microarray experiments. Statistical Applications in Genetics and Molecular Biology 3, No. 1, Article 3.

enrichreg, iChip2,iChip1

library(limma)

# load the log2 transformed and quantile-normalized Oct4 data 
data(oct4)
oct4[1:3,]

# calculate the enrichment measurements --- two-sample limma t-statistics
oct4lmt1 = lmtstat(oct4[,5:6],oct4[,3:4])

# calculate paired limma t-statistics for the data that are in
# the log-ratio format (e.g., log2(IP-enriched/control))

oct4log2r = oct4[,5:6] - oct4[,3:4]
oct4lmt2 = lmtstat(oct4log2r)