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

GSE47774 synthetic construct; Homo sapiens Expression profiling by high throughput sequencing 3396 samples Submitted 2014/08/08 Platform GPL11154Platform GPL14603Platform GPL16558Platform GPL15228Platform GPL17278
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 GSE47774_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 3396 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA208369 and SRA study SRP025982. Searching any of these in the dataset finder brings you back here.

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