QuickIsoSeq for Isoform Quantification in Large-Scale RNA Sequencing
- PMID: 33835441
- DOI: 10.1007/978-1-0716-1307-8_8
QuickIsoSeq for Isoform Quantification in Large-Scale RNA Sequencing
Erratum in
-
Correction to: RNA Bioinformatics.Methods Mol Biol. 2021;2284:C1. doi: 10.1007/978-1-0716-1307-8_32. Methods Mol Biol. 2021. PMID: 34339024 No abstract available.
Abstract
RNA-sequencing (RNA-seq) is a powerful technology for transcriptome profiling. While most RNA-seq projects focus on gene-level quantification and analysis, there is growing evidence that most mammalian genes are alternatively spliced to generate different isoforms that can be subsequently translated to protein molecules with diverse or even opposing biological functions. Quantifying the expression levels of these isoforms is key to understanding the genes biological functions in healthy tissues and the progression of diseases. Among open source tools developed for isoform quantification, Salmon, Kallisto, and RSEM are recommended based upon previous systematic evaluation of these tools using both experimental and simulated RNA-seq datasets. However, isoform quantification in practical RNA-seq data analysis needs to deal with many QC issues, such as the abundance of rRNAs in mRNA-seq, the efficiency of globin RNA depletion in whole blood samples, and potential sample swapping. To overcome these practical challenges, QuickIsoSeq was developed for large-scale RNA-seq isoform quantification along with QC. In this chapter, we describe the pipeline and detailed the steps required to deploy and use it to analyze RNA-seq datasets in practice. The QuickIsoSeq package can be downloaded from https://github.com/shanrongzhao/QuickIsoSeq.
Keywords: Isoform quantification; QuickIsoSeq; RNA-seq; RNA-seq pipeline.
References
-
- Mortazavi A et al (2008) Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat Methods 5(7):621–628 - DOI
-
- Stark R, Grzelak M, Hadfield J (2019) RNA sequencing: the teenage years. Nat Rev Genet 20(11):631–656 - DOI
-
- Wang ET et al (2008) Alternative isoform regulation in human tissue transcriptomes. Nature 456:470–476 - DOI
-
- Harrow J et al (2012) GENCODE: the reference human genome annotation for the ENCODE project. Genome Res 22:1760–1774 - DOI
-
- Aoubala M et al (2011) p53 directly transactivates Delta133p53alpha, regulating cell fate outcome in response to DNA damage. Cell Death Differ 18:248–258 - DOI
MeSH terms
Substances
LinkOut - more resources
Full Text Sources
Other Literature Sources
