A1 Refereed original research article in a scientific journal
Comparison of methods to detect differentially expressed genes between single-cell populations
Authors: Maria K. Jaakkola, Fatemeh Seyednasrollah, Arfa Mehmood, Laura L. Elo
Publication year: 2017
Journal: Briefings in Bioinformatics
Article number: bbw057
Volume: 18
Issue: 5
First page : 735
Last page: 743
Number of pages: 9
ISSN: 1467-5463
DOI: https://doi.org/10.1093/bib/bbw057
Web address : https://academic.oup.com/bib/article/18/5/735/2562772/Comparison-of-methods-to-detect-differentially
Self-archived copy’s web address: 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.
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