Autor según el artículo: Roca, C.P.; Gomes, S.I.L.; Amorim, M.J.B.; Scott-Fordsmand, J.J.

Departamento: Enginyeria Química

Autor/es de la URV: PEREZ ROCA, CARLOS; Gomes, S.I.L.; Amorim, M.J.B.; Scott-Fordsmand, J.J.

Palabras clave: gene expression profiling reproducibility Gene expression regulation

Resumen: 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.

Áreas temáticas: Enginyeria química Ingeniería química Chemical engineering

Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/

ISSN: 2045-2322

Identificador del autor: ; n/a; n/a; 0000-0002-2260-1224

Fecha de alta del registro: 2017-03-28

Volumen de revista: 7

Versión del articulo depositado: info:eu-repo/semantics/publishedVersion

Enlace a la fuente original: https://www.nature.com/articles/srep42460

DOI del artículo: 10.1038/srep42460

Entidad: Universitat Rovira i Virgili

Año de publicación de la revista: 2017

Tipo de publicación: Article Artículo Article