RT Journal Article
SR Electronic
T1 Beyond comparisons of means: understanding changes in gene expression at the single-cell level
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 035949
DO 10.1101/035949
A1 Catalina A. Vallejos
A1 Sylvia Richardson
A1 John C. Marioni
YR 2016
UL http://biorxiv.org/content/early/2016/01/05/035949.abstract
AB Single-cell RNA sequencing (scRNA-seq) can be used to characterise differences in gene expression patterns between pre-specified populations of cells. Traditionally, differential expression tools are restricted to the study of changes in overall expression between cell populations. However, such analyses do not take full advantage of the rich information provided by scRNA-seq. In this article, we present a Bayesian hierarchical model which can be used to study changes in expression that lie beyond comparisons of means. In particular, our method can highlight genes that undergo changes in cell-to-cell heterogeneity between the populations but whose overall expression is preserved. Evidence supporting these changes is quantified using a probabilistic approach based on tail posterior probabilities, where a probability cut-off is calibrated through the expected false discovery rate. Our method incorporates a built-in normalisation strategy and quantifies technical artefacts by borrowing information from technical spike-in genes. Control experiments validate the performance of our approach. Finally, we compare expression patterns of mouse embryonic stem cells between different stages of the cell cycle, revealing substantial differences in cellular heterogeneity.