gtPaired: Wrapper function for gt

In eLNNpaired: Model-Based Gene Clustering for Genomics Data from Paired/Matched Designs

Description

Wrapper function for the function gt in the Bioconductor package globaltest.

Usage

gtPaired(
  es, 
  alpha = 0.05, 
  pvalAdjMethod = "fdr")

Arguments

es	An ExpressionSet object stores within-pair log2 difference.
alpha	cutoff for adjusted p-value. If an adjusted pvalue is less than alpha, we claim this probe is significant.
pvalAdjMethod	character. indicating which p-value adjustment method will be used.

Value

A list with 3 elements:

resFrame	a data frame with 4 columns: probeid, stat, pval, and p.adj.
memGenes	3-cluster probe cluster membership. 1 indicates over-expressed probes; 2 indicates under-expressed probes; 3 indicates non-differentially expressed probes.
memGenes2	2-cluster probe cluster membership. 1 indicates differentially-expressed probes; 0 indicates non-differentially expressed probes.

Author(s)

Yunfeng Li <[e-mail]> and Weiliang Qiu <[e-mail]>

References

Li Y, Morrow J, Raby B, Tantisira K, Weiss ST, Huang W, Qiu W. (2017), <doi:10.1371/journal.pone.0174602>

Examples

set.seed(100)
G = 500
n = 10

delta_1 = -0.8184384  
xi_1 = -1.1858546 
lambda_1 = -10.6309216  
nu_1 = -3.5536255  

delta_2 = -0.8153614  
xi_2 = -1.4120148 
lambda_2 = -13.1999427  
nu_2 = -3.3873531   

lambda_3 = 0.7597441  
nu_3 = -2.0361091 

psi = c(delta_1, xi_1, lambda_1, nu_1,
        delta_2, xi_2, lambda_2, nu_2,
        lambda_3, nu_3)
t_pi = c(0.08592752, 0.07110449)

c1 = qnorm(0.95)
c2 = qnorm(0.05)

E_Set = gen_eLNNpaired(G, n, psi, t_pi, c1, c2)

result = gtPaired(es = E_Set)

print(table(result$memGenes, fData(E_Set)$memGenes.true))
print(table(result$memGenes2, fData(E_Set)$memGenes2.true))

eLNNpaired documentation built on May 29, 2017, 12:04 p.m.