RSeQC: quality control of RNA-seq experiments | Zendy

Liguo Wang | Zendy; Shengqin Wang | Zendy; Wei Li | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

RSeQC: quality control of RNA-seq experiments

Author(s) -

Liguo Wang,

Shengqin Wang,

Wei Li

Publication year - 2012

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/bts356

Subject(s) - python (programming language) , computer science , scripting language , rna seq , rna , source code , computational biology , data mining , software , transcriptome , biology , programming language , gene , genetics , gene expression

RNA-seq has been extensively used for transcriptome study. Quality control (QC) is critical to ensure that RNA-seq data are of high quality and suitable for subsequent analyses. However, QC is a time-consuming and complex task, due to the massive size and versatile nature of RNA-seq data. Therefore, a convenient and comprehensive QC tool to assess RNA-seq quality is sorely needed.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research