Benchmark analysis of algorithms for determining and quantifying full-length mRNA splice forms from RNA-seq data

Bioinformatics
Katharina E HayerGregory R Grant

Abstract

Because of the advantages of RNA sequencing (RNA-Seq) over microarrays, it is gaining widespread popularity for highly parallel gene expression analysis. For example, RNA-Seq is expected to be able to provide accurate identification and quantification of full-length splice forms. A number of informatics packages have been developed for this purpose, but short reads make it a difficult problem in principle. Sequencing error and polymorphisms add further complications. It has become necessary to perform studies to determine which algorithms perform best and which if any algorithms perform adequately. However, there is a dearth of independent and unbiased benchmarking studies. Here we take an approach using both simulated and experimental benchmark data to evaluate their accuracy. We conclude that most methods are inaccurate even using idealized data, and that no method is highly accurate once multiple splice forms, polymorphisms, intron signal, sequencing errors, alignment errors, annotation errors and other complicating factors are present. These results point to the pressing need for further algorithm development. Simulated datasets and other supporting information can be found at http://bioinf.itmat.upenn.edu/BEERS/bp2. Supple...Continue Reading

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Citations

Apr 14, 2015·Journal of Experimental Zoology. Part B, Molecular and Developmental Evolution·Julien RouxMarc Robinson-Rechavi
May 18, 2016·Marine Genomics·Rute R da FonsecaRicardo J Pereira
Nov 17, 2019·Life Science Alliance·Marina PinskayaAntonin Morillon
Jul 22, 2020·BMC Bioinformatics·Rongshan YuShun Wang
Apr 14, 2018·Genome Biology·Lynn YiLior Pachter
May 27, 2017·International Journal of Molecular Sciences·Wolfgang KaisersHeiner Schaal
Jul 20, 2018·G3 : Genes - Genomes - Genetics·Jeremy R B NewmanLauren M McIntyre
Jun 19, 2021·Genome Biology·Yu HuKai Wang
Aug 7, 2021·Biosensors·Yuri D IvanovAlexander I Archakov

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Datasets Mentioned

BETA
GSM1219408
GSM1219399

Methods Mentioned

BETA
RNA-Seq
CLASS
PCR
in vitro transcription

Software Mentioned

ABySS
FlipFlop
SOAPdenovo
CLCBio Genomics Workbench
RSEM
BEERS
HTSEQ
Oases
Trinity
STAR

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