当前位置： SCI文献检索 > BMC BIOINFORMATICS期刊下所有文献 > Investigating the concordance of Gene Ontology terms reveals the intra- and inter-platform reproducibility of enrichment analysis.

Investigating the concordance of Gene Ontology terms reveals the intra- and inter-platform reproducibility of enrichment analysis.

Abstract：

BACKGROUND:Reliability and Reproducibility of differentially expressed genes (DEGs) are essential for the biological interpretation of microarray data. The microarray quality control (MAQC) project launched by US Food and Drug Administration (FDA) elucidated that the lists of DEGs generated by intra- and inter-platform comparisons can reach a high level of concordance, which mainly depended on the statistical criteria used for ranking and selecting DEGs. Generally, it will produce reproducible lists of DEGs when combining fold change ranking with a non-stringent p-value cutoff. For further interpretation of the gene expression data, statistical methods of gene enrichment analysis provide powerful tools for associating the DEGs with prior biological knowledge, e.g. Gene Ontology (GO) terms and pathways, and are widely used in genome-wide research. Although the DEG lists generated from the same compared conditions proved to be reliable, the reproducible enrichment results are still crucial to the discovery of the underlying molecular mechanism differentiating the two conditions. Therefore, it is important to know whether the enrichment results are still reproducible, when using the lists of DEGs generated by different statistic criteria from inter-laboratory and cross-platform comparisons. In our study, we used the MAQC data sets for systematically accessing the intra- and inter-platform concordance of GO terms enriched by Gene Set Enrichment Analysis (GSEA) and LRpath. RESULTS:In intra-platform comparisons, the overlapped percentage of enriched GO terms was as high as ~80% when the inputted lists of DEGs were generated by fold change ranking and Significance Analysis of Microarrays (SAM), whereas the percentages decreased about 20% when generating the lists of DEGs by using fold change ranking and t-test, or by using SAM and t-test. Similar results were found in inter-platform comparisons. CONCLUSIONS:Our results demonstrated that the lists of DEGs in a high level of concordance can ensure the high concordance of enrichment results. Importantly, based on the lists of DEGs generated by a straightforward method of combining fold change ranking with a non-stringent p-value cutoff, enrichment analysis will produce reproducible enriched GO terms for the biological interpretation.

journal_name

BMC Bioinformatics

journal_title

BMC bioinformatics

authors

Zhang L,Zhang J,Yang G,Wu D,Jiang L,Wen Z,Li M

doi

10.1186/1471-2105-14-143

subject

Has Abstract

pub_date

2013-04-29 00:00:00

pages

143

issn

1471-2105

pii

1471-2105-14-143

journal_volume

pub_type

杂志文章

在线工具

Investigating the concordance of Gene Ontology terms reveals the intra- and inter-platform reproducibility of enrichment analysis.