Journal
NATURE BIOTECHNOLOGY
Volume 31, Issue 11, Pages 1015-+Publisher
NATURE PUBLISHING GROUP
DOI: 10.1038/nbt.2702
Keywords
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Funding
- European Commission [261123]
- Swiss National Science Foundation [130326, 130342]
- Louis Jeantet Foundation
- ERC [260927, 294653]
- NIH-NIMH [MH090941]
- Spanish Plan Nacional [SAF2008-00357, BIO2011-26205]
- Generalitat de Catalunya AGAUR [SGR-1502]
- Instituto de Salud Carlos III [FIS/FEDER PI11/00733]
- ESGI, READNA [Health-F4-2008-201418]
- Spanish Ministry of Economy and Competitiveness (MINECO)
- Generalitat de Catalunya
- Centre for Medical Systems Biology within the framework of The Netherlands Genomics Initiative (NGI)/Netherlands Organisation for Scientific Research (NWO)
- Swedish Research Council [C0524801, A028001]
- Knut and Alice Wallenberg Foundation [2011.0073]
- EMBO long-term fellowship [ALTF 225-2011]
- Emil Aaltonen Foundation and Academy of Finland fellowships
- SNP&SEQ Technology Platform in Uppsala
- [FP7/2007-2013]
- [HEALTH-F4-2007-201413]
- European Research Council (ERC) [294653, 260927] Funding Source: European Research Council (ERC)
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RNA sequencing is an increasingly popular technology for genome-wide analysis of transcript sequence and abundance. However, understanding of the sources of technical and interlaboratory variation is still limited. To address this, the GEUVADIS consortium sequenced mRNAs and small RNAs of lymphoblastoid cell lines of 465 individuals in seven sequencing centers, with a large number of replicates. The variation between laboratories appeared to be considerably smaller than the already limited biological variation. Laboratory effects were mainly seen in differences in insert size and GC content and could be adequately corrected for. In small-RNA sequencing, the microRNA ( miRNA) content differed widely between samples owing to competitive sequencing of rRNA fragments. This did not affect relative quantification of miRNAs. We conclude that distributing RNA sequencing among different laboratories is feasible, given proper standardization and randomization procedures. We provide a set of quality measures and guidelines for assessing technical biases in RNA-seq data.
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