PT  - JOURNAL ARTICLE
AU  - Sengupta, Debarka
AU  - Rayan, Nirmala Arul
AU  - Lim, Michelle
AU  - Lim, Bing
AU  - Prabhakar, Shyam
TI  - Fast, scalable and accurate differential expression analysis for single cells
AID  - 10.1101/049734
DP  - 2016 Jan 01
TA  - bioRxiv
PG  - 049734
4099  - http://biorxiv.org/content/early/2016/04/22/049734.short
4100  - http://biorxiv.org/content/early/2016/04/22/049734.full
AB  - Analysis of single-cell RNA-seq data is challenging due to technical variability, high noise levels and massive sample sizes. Here, we describe a normalization technique that substantially reduces technical variability and improves the quality of downstream analyses. We also introduce a nonparametric method for detecting differentially expressed genes that scales to > 1,000 cells and is both more accurate and ~10 times faster than existing parametric approaches.