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Cross-platform ultradeep transcriptomic profiling of human reference RNA samples by RNA-Seq

Authors :
Huixiao Hong
Danielle Thierry-Mieg
David P. Kreil
Christopher E. Mason
Leming Shi
Jean Thierry-Mieg
Joshua Xu
Weida Tong
Zhenqiang Su
Source :
Scientific Data
Publication Year :
2014
Publisher :
Springer Science and Business Media LLC, 2014.

Abstract

Whole-transcriptome sequencing (‘RNA-Seq’) has been drastically changing the scale and scope of genomic research. In order to fully understand the power and limitations of this technology, the US Food and Drug Administration (FDA) launched the third phase of the MicroArray Quality Control (MAQC-III) project, also known as the SEquencing Quality Control (SEQC) project. Using two well-established human reference RNA samples from the first phase of the MAQC project, three sequencing platforms were tested across more than ten sites with built-in truths including spike-in of external RNA controls (ERCC), titration data and qPCR verification. The SEQC project generated over 30 billion sequence reads representing the largest RNA-Seq data ever generated by a single project on individual RNA samples. This extraordinarily ultradeep transcriptomic data set and the known truths built into the study design provide many opportunities for further research and development to advance the improvement and application of RNA-Seq.

Details

Language :
English
ISSN :
20524463
Volume :
1
Database :
OpenAIRE
Journal :
Scientific Data
Accession number :
edsair.doi.dedup.....7ccf68b1ae1b238f849f6846179facc9
Full Text :
https://doi.org/10.1038/sdata.2014.20