Do count-based differential expression methods perform poorly when genes are expressed in only one condition?

Xiaobei Zhou^1,2 and Mark D. Robinson^1,2,*

¹ Institute of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190 CH-8057 Zurich, Switzerland
² SIB Swiss Institute of Bioinformatics, University of Zurich, Zurich, Switzerland

^* Corresponding author: mark.robinson@imls.uzh.ch.

Summary

A Correspondence to Comprehensive evaluation of differential gene expression analysis methods for RNA-seq data by Rapaport F, Khanin R, Liang Y, Pirun M, Krek A, Zumbo P, Mason CE, Socci ND and Betel D
Genome Biol 2013, 14:R95

Supplement

biorXiv document: http://biorxiv.org/content/early/2015/04/07/017673

Additional Files:
Additional file 1 ---Table of statistics for zero-count genes
Table of zero counts, differential statistics and S/N for the ENCODE dataset

Additional file 2 ---Supplementary Figures
This file contains the mentioned Supplementary Figures.

Additional material ---R code and data
This file contains R code and necessary data used to reproduce the figures in the main manuscript and in the supplement.

Do count-based differential expression methods perform poorly when genes are expressed in only one condition?

Xiaobei Zhou1,2 and Mark D. Robinson1,2,*

Summary

Supplement

Xiaobei Zhou^1,2 and Mark D. Robinson^1,2,*