Multi-perspective quality control of Illumina RNA sequencing data analysis.
AUTHORS
- NIHMSID: 101528229
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.
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.
Tags: Faculty Publications 2016