Multi-perspective quality control of Illumina RNA sequencing data analysis

Quanhu Sheng, Kasey C. Vickers, Shilin Zhao, Jing Wang, David C. Samuels, Olivia I. Koues, Yu Shyr, Yan Guo

Briefings in Functional Genomics · 2016 · 118 citations · 69 references

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Abstract

Quality control (QC) is a critical step in RNA sequencing (RNA-seq). Yet, it is often ignored or conducted on a limited basis. Here, we present a multi-perspective strategy for QC of RNA-seq experiments. The QC of RNA-seq can be divided into four related stages: (1) RNA quality, (2) raw read data (FASTQ), (3) alignment and (4) gene expression. We illustrate the importance of conducting QC at each stage of an RNA-seq experiment and demonstrate our recommended RNA-seq QC strategy. Furthermore, we discuss the major and often neglected quality issues associated with the three major types of RNA-seq: mRNA, total RNA and small RNA. This RNA-seq QC overview provides comprehensive guidance for researchers who conduct RNA-seq experiments.

References

69