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




Maria K. Jaakkola, Fatemeh Seyednasrollah, Arfa Mehmood, Laura L. Elo

2017

Briefings in Bioinformatics

bbw057

18

5

735

743

9

1467-5463

DOIhttps://doi.org/10.1093/bib/bbw057

https://academic.oup.com/bib/article/18/5/735/2562772/Comparison-of-methods-to-detect-differentially

https://research.utu.fi/converis/portal/detail/Publication/18174166



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.


Last updated on 2024-26-11 at 14:38