September 2014 – Ana Conesa Lab – Assessing technical performance in differential gene expression experiments with external spike-in RNA control ratio mixtures
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.
Learn more about Dr. Ana Conesa!
My research focuses on the understanding of the functional aspects of gene expression at the genome-wide level and across different organisms. My group has developed statistical methods and software tools that analyse transcriptome dynamics, functional annotation and omcis data integration. We have developed bioinformatics tools such as Blast2GO, maSigPro, Paintomcis and NOISeq, among others.
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