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

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 an...

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Detalles Bibliográficos
Autores principales: Jaakkola, Maria K, Seyednasrollah, Fatemeh, Mehmood, Arfa, Elo, Laura L
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5862313/
https://www.ncbi.nlm.nih.gov/pubmed/27373736
http://dx.doi.org/10.1093/bib/bbw057
Descripción
Sumario: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.