RT Journal Article
SR Electronic
T1 scImpute: accurate and robust imputation for single cell RNA-seq data
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 141598
DO 10.1101/141598
A1 Wei Vivian Li
A1 Jingyi Jessica Li
YR 2017
UL http://biorxiv.org/content/early/2017/06/04/141598.abstract
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.