Multi-perspective quality control of Illumina RNA sequencing data analysis

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

Research output: Contribution to journalArticlepeer-review

30 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)194-204
Number of pages11
JournalBriefings in functional genomics
Volume16
Issue number4
DOIs
Publication statusPublished - 2017

All Science Journal Classification (ASJC) codes

  • Biochemistry
  • Molecular Biology
  • Genetics

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