Change search
ReferencesLink to record
Permanent link

Direct link
Assessing the consistency of public human tissue RNA-seq data sets
KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. (Involved Human Prot Atlas Project)
2015 (English)In: Briefings in Bioinformatics, ISSN 1467-5463, E-ISSN 1477-4054, Vol. 16, no 6, 941-949 p.Article in journal (Refereed) PublishedText
Abstract [en]

Sequencing-based gene expression methods like RNA-sequencing (RNA-seq) have become increasingly common, but it is often claimed that results obtained in different studies are not comparable owing to the influence of laboratory batch effects, differences in RNA extraction and sequencing library preparation methods and bioinformatics processing pipelines. It would be unfortunate if different experiments were in fact incomparable, as there is great promise in data fusion and meta-analysis applied to sequencing data sets. We therefore compared reported gene expression measurements for ostensibly similar samples (specifically, human brain, heart and kidney samples) in several different RNA-seq studies to assess their overall consistency and to examine the factors contributing most to systematic differences. The same comparisons were also performed after preprocessing all data in a consistent way, eliminating potential bias from bioinformatics pipelines. We conclude that published human tissue RNA-seq expression measurements appear relatively consistent in the sense that samples cluster by tissue rather than laboratory of origin given simple preprocessing transformations. The article is supplemented by a detailed walkthrough with embedded R code and figures.

Place, publisher, year, edition, pages
Oxford University Press, 2015. Vol. 16, no 6, 941-949 p.
Keyword [en]
RNA-seq, public data, meta-analysis, gene expression, clustering
National Category
Biochemistry and Molecular Biology Computational Mathematics
URN: urn:nbn:se:kth:diva-180145DOI: 10.1093/bib/bbv017ISI: 000365708700005PubMedID: 25829468OAI: diva2:893752

QC 20160113

Available from: 2016-01-13 Created: 2016-01-07 Last updated: 2016-01-13Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textPubMed

Search in DiVA

By author/editor
Danielsson, Frida
By organisation
Proteomics and Nanobiotechnology
In the same journal
Briefings in Bioinformatics
Biochemistry and Molecular BiologyComputational Mathematics

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 17 hits
ReferencesLink to record
Permanent link

Direct link