Author, as appears in the article.: Roca, C.P.; Gomes, S.I.L.; Amorim, M.J.B.; Scott-Fordsmand, J.J.

Department: Enginyeria Química

URV's Author/s: PEREZ ROCA, CARLOS; Gomes, S.I.L.; Amorim, M.J.B.; Scott-Fordsmand, J.J.

Keywords: gene expression profiling reproducibility Gene expression regulation

Abstract: RNA-Seq and gene expression microarrays provide comprehensive profiles of gene activity, but lack of reproducibility has hindered their application. A key challenge in the data analysis is the normalization of gene expression levels, which is currently performed following the implicit assumption that most genes are not differentially expressed. Here, we present a mathematical approach to normalization that makes no assumption of this sort. We have found that variation in gene expression is much larger than currently believed, and that it can be measured with available assays. Our results also explain, at least partially, the reproducibility problems encountered in transcriptomics studies. We expect that this improvement in detection will help efforts to realize the full potential of gene expression profiling, especially in analyses of cellular processes involving complex modulations of gene expression.

Thematic Areas: Enginyeria química Ingeniería química Chemical engineering

licence for use: https://creativecommons.org/licenses/by/3.0/es/

ISSN: 2045-2322

Author identifier: ; n/a; n/a; 0000-0002-2260-1224

Record's date: 2017-03-28

Journal volume: 7

Papper version: info:eu-repo/semantics/publishedVersion

Link to the original source: https://www.nature.com/articles/srep42460

Article's DOI: 10.1038/srep42460

Entity: Universitat Rovira i Virgili

Journal publication year: 2017

Publication Type: Article Artículo Article