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A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequence Quality Control consortium

GSE56457 Homo sapiens Expression profiling by array; Expression profiling by RT-PCR 60 samples Submitted 2014/08/08 Platform GPL17930Platform GPL18522Platform GPL16043Platform GPL10558
Summary
We present primary results from the Sequencing Quality Control (SEQC) project, coordinated by the United States Food and Drug Administration. Examining Illumina HiSeq, Life Technologies SOLiD and Roche 454 platforms at multiple laboratory sites using reference RNA samples with built-in controls, we assess RNA sequencing (RNA-seq) performance for sequence discovery and differential expression profiling and compare it to microarray and quantitative PCR (qPCR) data using complementary metrics. At all sequencing depths, we discover unannotated exon-exon junctions, with >80% validated by qPCR. We find that measurements of relative expression are accurate and reproducible across sites and platforms if specific filters are used. In contrast, RNA-seq and microarrays do not provide accurate absolute measurements, and gene-specific biases are observed, for these and qPCR. Measurement performance depends on the platform and data analysis pipeline, and variation is large for transcriptlevel profiling. The complete SEQC data sets, comprising >100 billion reads (10Tb), provide unique resources for evaluating RNA-seq analyses for clinical and regulatory settings.
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Direct links to NCBI, no account and no request form: the whole study as GSE56457_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 60 samples.

Also filed as BioProject PRJNA243413. Searching any of these in the dataset finder brings you back here.

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