Comparison of methods to detect differentially expressed genes between single-cell populations

Briefings in Bioinformatics
Maria K JaakkolaLaura L Elo

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.

References

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Citations

Sep 10, 2017·Cell and Tissue Research·Ting Zhou, Hiroaki Matsunami
Mar 27, 2018·Briefings in Functional Genomics·Christoph ZiegenhainWolfgang Enard
Oct 14, 2017·Briefings in Bioinformatics·Daniel SpiesConstance Ciaudo
Jun 8, 2017·Frontiers in Genetics·Alessandra Dal MolinBarbara Di Camillo
Feb 27, 2018·Genome Biology·Koen Van den BergeLieven Clement

Related Concepts

RNA
Reproducibility of Results
Gene Expression
Sequence Determinations, RNA
MRNA Differential Display
Single-Cell Analysis
Genes
RNA
Research Methodology
Analysis

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