Impact of RNA-seq data analysis algorithms on gene expression estimation and downstream prediction.
Li Tong, Po-Yen Wu, John H Phan, Hamid R Hassazadeh, undefined SEQC Consortium, Weida Tong, May D Wang
Scientific Reports | Published : 2020
To use next-generation sequencing technology such as RNA-seq for medical and health applications, choosing proper analysis methods for biomarker identification remains a critical challenge for most users. The US Food and Drug Administration (FDA) has led the Sequencing Quality Control (SEQC) project to conduct a comprehensive investigation of 278 representative RNA-seq data analysis pipelines consisting of 13 sequence mapping, three quantification, and seven normalization methods. In this article, we focused on the impact of the joint effects of RNA-seq pipelines on gene expression estimation as well as the downstream prediction of disease outcomes. First, we developed and applied three metr..View full abstract