Microarray vs. RNA-Seq: a comparison for active subnetwork discovery

Authors:
Ayat Hatem;Kamer Kaya;Ümit V. Çatalyürek
Affiliations:
The Ohio State University, Columbus, OH;The Ohio State University, Columbus, OH;The Ohio State University, Columbus, OH
Venue:
Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine
Year:
2012

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Abstract

While microarrays have been successfully used by the researchers to analyze gene expression levels, cutting edge high throughput sequencing technologies now made it possible to go one step further. Recent studies show that absolute expression levels are not accurately estimated by microarray data. In this work, we elaborate various experiments to compare highly-active subnetworks in protein-protein interaction networks found by the state-of-the-art tools used with microarray or RNA-Seq data. Our experiments show that RNA-Seq data can be important to detect active networks which are overlooked by the microarray data. Furthermore, these networks can contain genes which are biologically proved to be significant. However, we also observed that when the RNA-Seq data is used, the subnetworks found by the tools may not be effective as biomarkers due to their large sizes. Hence, some changes in the algorithms incorporated in current tools may be necessary while working with RNA-Seq data.