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Quantitative Biology

, Volume 4, Issue 4, pp 243–260 | Cite as

Differential expression analyses for single-cell RNA-Seq: old questions on new data

  • Zhun Miao
  • Xuegong Zhang
Research Article

Abstract

Background

Single-cell RNA sequencing (scRNA-seq) is an emerging technology that enables high resolution detection of heterogeneities between cells. One important application of scRNA-seq data is to detect differential expression (DE) of genes. Currently, some researchers still use DE analysis methods developed for bulk RNA-Seq data on single-cell data, and some new methods for scRNA-seq data have also been developed. Bulk and single-cell RNA-seq data have different characteristics. A systematic evaluation of the two types of methods on scRNA-seq data is needed.

Results

In this study, we conducted a series of experiments on scRNA-seq data to quantitatively evaluate 14 popular DE analysis methods, including both of traditional methods developed for bulk RNA-seq data and new methods specifically designed for scRNA-seq data. We obtained observations and recommendations for the methods under different situations.

Conclusions

DE analysis methods should be chosen for scRNA-seq data with great caution with regard to different situations of data. Different strategies should be taken for data with different sample sizes and/or different strengths of the expected signals. Several methods for scRNA-seq data show advantages in some aspects, and DEGSeq tends to outperform other methods with respect to consistency, reproducibility and accuracy of predictions on scRNA-seq data.

Keywords

single-cell RNA-Seq differential expression 

Supplementary material

40484_2016_89_MOESM1_ESM.pdf (34.6 mb)
Differential expression analyses for single-cell RNA-Seq: old questions on new data

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Copyright information

© Higher Education Press and Springer-Verlag GmbH 2016

Authors and Affiliations

  1. 1.MOE Key Laboratory of Bioinformatics; Bioinformatics Division and Center for Synthetic & Systems Biology, TNLIST; Department of AutomationTsinghua UniversityBeijingChina
  2. 2.School of Life SciencesTsinghua UniversityBeijingChina

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