corfdrci {GeneNT} | R Documentation |
This function implements the two-stage screening procedure based on Pearson correlation coefficient to screen similarly co-expressed gene pairs. Specifying a pair of FDR and MAS criteria, the algorithm provides an initial co-expression discovery that controls only FDR, which is then followed by a second stage co-expression discovery which controls both FDR and MAS.
corfdrci(Q, cormin, method)
Q |
The significant level |
cormin |
The specified minimum acceptable strength of association measured using Pearson correlation coefficient |
method |
The multiple comparison adjustment methods, eg, "BH" (for independent tests) and "BY" (for general dependent tests) |
The data matrix file must be in the right format. The first row (header) must be one shorter than the rest rows. The first column must be gene names.
The function returns a list of gene pairs that satisfies the FDR and MAS criteria simultaneously measured by Pearson correlation statistic.
pG1 |
The gene pairs that passes Stage I (FDR only) screening |
pG2 |
The gene pairs that passed both Stage I (FDR) and II (MAS) screenings |
Dongxiao Zhu (http://dongxiaozhu.googlepages.com/home)
Fisher, R.A. (1921). On the 'probable error' of a coefficient of correlation deduced from a small sample. Metron, 1, 1–32. Zhu, D., Hero, A.O., Qin, Z.S. and Swaroop, A. High throughput screening of co-expressed gene pairs with controlled False Discovery Rate (FDR) and Minimum Acceptable Strength (MAS). J Comput Biol, 12, 1027-1043.
## load GeneNT library library(GeneNT) ## load the example dataset data(dat) ## Note, data matrix name has to be "dat" ## use (FDR, MAS) criteria (0.2, 0.5) as example to screen gene pairs ## multiple tests adjustment method is "BY" g1 <- corfdrci(0.2, 0.5, "BY") pG1 <- g1$pG1 ## pG2 contains gene pairs that passed two-stage screening pG2 <- g1$pG2