A1 Refereed original research article in a scientific journal

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




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

Publication year2017

JournalBriefings in Bioinformatics

Article numberbbw057

Volume18

Issue5

First page 735

Last page743

Number of pages9

ISSN1467-5463

DOIhttps://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 addresshttps://research.utu.fi/converis/portal/detail/Publication/18174166


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.


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