| Literature DB >> 25254650 |
Sarah A Munro1, Steven P Lund2, P Scott Pine1, Hans Binder3, Djork-Arné Clevert4, Ana Conesa5, Joaquin Dopazo6, Mario Fasold7, Sepp Hochreiter4, Huixiao Hong8, Nadereh Jafari9, David P Kreil10, Paweł P Łabaj11, Sheng Li12, Yang Liao13, Simon M Lin14, Joseph Meehan8, Christopher E Mason12, Javier Santoyo-Lopez15, Robert A Setterquist16, Leming Shi17, Wei Shi18, Gordon K Smyth19, Nancy Stralis-Pavese11, Zhenqiang Su8, Weida Tong8, Charles Wang20, Jian Wang21, Joshua Xu8, Zhan Ye22, Yong Yang21, Ying Yu17, Marc Salit1.
Abstract
There is a critical need for standard approaches to assess, report and compare the technical performance of genome-scale differential gene expression experiments. Here we assess technical performance with a proposed standard 'dashboard' of metrics derived from analysis of external spike-in RNA control ratio mixtures. These control ratio mixtures with defined abundance ratios enable assessment of diagnostic performance of differentially expressed transcript lists, limit of detection of ratio (LODR) estimates and expression ratio variability and measurement bias. The performance metrics suite is applicable to analysis of a typical experiment, and here we also apply these metrics to evaluate technical performance among laboratories. An interlaboratory study using identical samples shared among 12 laboratories with three different measurement processes demonstrates generally consistent diagnostic power across 11 laboratories. Ratio measurement variability and bias are also comparable among laboratories for the same measurement process. We observe different biases for measurement processes using different mRNA-enrichment protocols.Mesh:
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Year: 2014 PMID: 25254650 DOI: 10.1038/ncomms6125
Source DB: PubMed Journal: Nat Commun ISSN: 2041-1723 Impact factor: 14.919