A survey of best practices for RNA-seq data analysis

Article, Review English OPEN
Conesa, Ana; Madrigal, Pedro; Tarazona, Sonia; Gomez-Cabrero, David; Cervera, Alejandra; McPherson, Andrew; Szcześniak, Michał Wojciech; Gaffney, Daniel J.; Elo, Laura L.; Zhang, Xuegong; Mortazavi, Ali;
(2016)
  • Publisher: Springer Nature
  • Journal: Genome Biology,volume 17,issue 1 (issn: 1474-760X, eissn: 1474-760X)
  • Publisher copyright policies & self-archiving
  • Related identifiers: doi: 10.1186/s13059-016-1047-4, doi: 10.1186/s13059-016-0881-8, pmc: PMC4728800
  • Subject: SYSTEMS BIOLOGY | DNA-METHYLATION | Next-generation sequencing | GENOME BROWSER | 318 Medical biotechnology | standards | differential gene expression | INTEGRATED ANALYSIS MMIA | Review | PROSTATE-CANCER | transcriptomics | SINGLE-CELL | guidelines | DEEP SEQUENCING DATA | LARGE GENE LISTS | WEB-BASED TOOL | DIFFERENTIAL EXPRESSION ANALYSIS | RNA-seq

RNA-sequencing (RNA-seq) has a wide variety of applications, but no single analysis pipeline can be used in all cases. We review all of the major steps in RNA-seq data analysis, including experimental design, quality control, read alignment, quantification of gene and t... View more
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