Exon-level estimates improve the detection of differentially expressed genes in RNA-seq studies
Author:
Affiliation:
1. Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland
2. Institute of Biomedicine, University of Turku, Turku, Finland
Funder
European Research Council ERC
European Union’s Horizon 2020 research and innovation programme
Academy of Finland
Juvenile Diabetes Research Foundation JDRF
Sigrid Juselius Foundation
University of Turku
Åbo Akademi University
Turku Graduate School
Biocenter Finland
ELIXIR Finland
Publisher
Informa UK Limited
Subject
Cell Biology,Molecular Biology
Link
https://www.tandfonline.com/doi/pdf/10.1080/15476286.2020.1868151
Reference30 articles.
1. Advanced Applications of RNA Sequencing and Challenges
2. Computational methods for transcriptome annotation and quantification using RNA-seq
3. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
4. limma powers differential expression analyses for RNA-sequencing and microarray studies
5. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data
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