Fisher's combined p-value for detecting differentially expressed genes using Affymetrix expression arrays

Abstract

Background: Currently, most tests of differential gene expression using Affymetrix expression array data are performed using expression summary values representing each probe set on a microarray. Recently testing methods have been proposed which incorporate probe level information. We propose a new approach that uses Fisher's method of combining evidence from multiple sources of information. Specifically, we combine p-values from probe level tests of significance.

Diffuse large B-cell lymphomas with CDKN2A deletion have a distinct gene expression signature and a poor prognosis under R-CHOP treatment: a GELA study

“…24 The Fisher combined P value approach was used to decipher common signatures between the 2 datasets. 25 …”

“…Considering the fact that almost all DLBCL 9p21 cases belong to the ABC subtype in this external series (21/25 DLBCL 9p21 ), we combined the results of the differential expression analyses of the 2 datasets to identify a common set of genes able to predict the CDKN2A/CDKN2B allelic status in ABC lymphoma cases. 25 Using this approach, we defined a list of 33 probe sets (corresponding to 28 genes including CDKN2A) that classifies our ABC DLBCL samples and the independent set of ABC DLBCL samples according to their 9p21 allelic status with unsupervised hierarchical clustering. Importantly, this set of genes remains efficient after exclusion of CDKN2A and defines a branch within the hierarchic clustering containing, respectively 15 (88%) of 17 and 14 (66%) of 21 ABC DLBCL 9p21del cases ( Figure 7C-D).…”

Integrating P-values for Genetic and Genomic Data Analysis

“…By Yu et al [15], permutation testing was used to determine the optimal number of k smallest p-values for a product test. In Hess and Iyer [16], Fisher's method was extended to Affymetrix gene expression arrays and shown to be a suitable diagnostic tool for exploratory analysis of microarray data. The combined p-value method was shown to be favorable versus competing methods through validated microarray data analyses.…”

An island-based approach for RNA-SEQ differential expression analysis.

“…Thus, if none of the islands are DE, the p-values p i are independent and uniformly distributed on the unit interval p i ∼ U (0, 1) which indicates the null hypothesis H 0 is true. Hence, χ 2 2k,p denotes the upper p point of the probability of a chi-squared distribution with 2k degrees of freedom [158,28,62].…”

“…This will ensure that regions in the gene will not be treated equally. Hess et al [62] proposed using Fisher's method to combine the significance of probe level tests to identify DE genes using Affymetrix arrays. Li and Tseng [83] proposed an adaptively weighted statistics method to combine multiple genomic studies for detecting differentially expressed genes.…”