title: Comparison of methods to detect differentially expressed genes between single-cell populations.
abstract: We compared five statistical methods to detect differentially expressed genes between two distinct single-cell populations. Currently, it remains unclear whether differential expression methods developed originally for conventional bulk RNA-seq data can also be applied to single-cell RNA-seq data analysis. Our results in three diverse comparison settings showed marked differences between the different methods in terms of the number of detections as well as their sensitivity and specificity. They, however, did not reveal systematic benefits of the currently available single-cell-specific methods. Instead, our previously introduced reproducibility-optimization method showed good performance in all comparison settings without any single-cell-specific modifications.
authors.forename: Maria K
authors.initials: MK
authors.lastname: Jaakkola
authors.forename: Fatemeh
authors.initials: F
authors.lastname: Seyednasrollah
authors.forename: Arfa
authors.initials: A
authors.lastname: Mehmood
authors.forename: Laura L
authors.initials: LL
authors.lastname: Elo
mesh_terms: D015870:Gene Expression; D020869:Gene Expression Profiling; D012313:RNA; D015203:Reproducibility of Results; D017423:Sequence Analysis, RNA; D059010:Single-Cell Analysis
chemical_list: D012313:RNA
keywords: RNA-seq; comparison; differential expression; reproducibility; single-cell