PT - JOURNAL ARTICLE AU - Wei Vivian Li AU - Jingyi Jessica Li TI - scImpute: accurate and robust imputation for single cell RNA-seq data AID - 10.1101/141598 DP - 2017 Jan 01 TA - bioRxiv PG - 141598 4099 - http://biorxiv.org/content/early/2017/06/04/141598.short 4100 - http://biorxiv.org/content/early/2017/06/04/141598.full AB - The analysis of single-cell RNA-seq (scRNA-seq) data is complicated and biased by excess zero or near zero counts, the so-called dropouts due to the low amounts of mRNA sequenced within individual cells. We introduce scImpute, a statistical method to accurately and robustly impute the dropouts in scRNA-seq data. scImpute is shown as an effective tool to enhance the clustering of cell populations, improve the accuracy of differential expression analysis, and aid the study of gene expression dynamics in time series scRNA-seq experiments.