Affiliation:
1. Center for Biostatistics, Department of Biomedical Informatics, The Ohio State University, Columbus, OH, USA
Abstract
With the widespread RNA-seq applications of different sequencing platforms in biomedical science research in recent years, a systematic evaluation of RNA-seq data quality is crucial and timely. The Sequencing Quality Control (SEQC) project is a large-scale community effort for assessing the performance of RNA-seq technology across different platforms and multiple laboratories, where reference RNA samples with multiple replicates were sequenced at 12 laboratories using 3 sequencing platforms. Different from the SEQC project, we performed an independent and comprehensive analysis of RNA-seq data of the SEQC project to assess sequencing reproducibility across platforms, sequencing sites, sample replicates, and FlowCells, respectively. With the employment of graphical tools and statistical models, our systemic analysis supports a distinctive conclusion that reproducibility across platforms and sequencing sites are not acceptable, whereas reproducibility across sample replicates and FlowCells are acceptable.
Cited by
5 articles.
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