Detecting expressed genes in cell populations at the single-cell level with scGeneXpress.

bioinformatics; cell identity; cell markers; discretization; gene expression; single cell RNAseq; Humans; Animals; Mice; Gene Expression Profiling/methods; Sequence Analysis, RNA/methods; Software; Single-Cell Analysis/methods

Abstract :

[en] Determining whether genes are expressed or not remains a challenge in single-cell RNAseq experiments due to their different expression spectra, which are influenced by genetics, the microenvironment and gene length. Current approaches for addressing this issue fail to provide a comprehensive landscape of expressed genes, since they neglect the inherent differences in the expression ranges and distributions of genes. Here, we present scGeneXpress, a method for detecting expressed genes in cell populations of single-cell RNAseq samples based on gene-specific reference distributions. We demonstrate that scGeneXpress accurately detects expressed cell markers and identity genes in 34 human and mouse tissues and can be employed to improve differential expression analysis of single-cell RNAseq data.

Disciplines :

Life sciences: Multidisciplinary, general & others

Author, co-author :

JUNG, Sascha ; University of Luxembourg > Faculty of Science, Technology and Medicine > Department of Life Sciences and Medicine ; Computational Biology Group, CIC bioGUNE-BRTA (Basque Research and Technology Alliance), Parque Cientifico Tecnologico de Bizkaia 801A, 48160 Derio, Spain

BARLIER, Celine ; University of Luxembourg > Luxembourg Centre for Systems Biomedicine > Computational Biology > Team Antonio DEL SOL MESA

Martinez Perez, Aitor ; Computational Biology Group, CIC bioGUNE-BRTA (Basque Research and Technology Alliance), Parque Cientifico Tecnologico de Bizkaia 801A, 48160 Derio, Spain

DEL SOL MESA, Antonio ; University of Luxembourg ; Computational Biology Group, CIC bioGUNE-BRTA (Basque Research and Technology Alliance), Parque Cientifico Tecnologico de Bizkaia 801A, 48160 Derio, Spain ; Ikerbasque, Basque Foundation for Science, Plaza Euskadi 5, 48009 Bilbao, Bizkaia, Spain

External co-authors :

yes

Language :

English

Title :

Detecting expressed genes in cell populations at the single-cell level with scGeneXpress.

Publication date :

23 September 2024

Journal title :

Briefings in Bioinformatics

ISSN :

1467-5463

eISSN :

1477-4054

Publisher :

Oxford University Press (OUP), England

Volume :

Issue :

Peer reviewed :

Peer Reviewed verified by ORBi

Additional URL :

https://academic.oup.com/bib/article-pdf/25/6/bbae494/59600159/bbae494.pdf

Funders :

New Frontiers in Research Fund
Spanish Ministry of Science and Innovation
Luxembourg National Research Fund

Available on ORBilu :

since 08 October 2024

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