APAtrap: identification and quantification of alternative polyadenylation sites from RNA-seq data
Autor: | Xiaohui Wu, Guoli Ji, Congting Ye, Yuqi Long, Qingshun Quinn Li |
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Rok vydání: | 2018 |
Předmět: |
0301 basic medicine
Statistics and Probability Untranslated region Polyadenylation Computer science Sequence analysis Arabidopsis RNA-Seq Computational biology Biochemistry Genome Transcriptome 03 medical and health sciences 0302 clinical medicine Humans Molecular Biology Gene Regulation of gene expression Sequence Analysis RNA Computer Science Applications Computational Mathematics Identification (information) 030104 developmental biology Computational Theory and Mathematics Poly A Software 030217 neurology & neurosurgery |
Zdroj: | Bioinformatics. 34:1841-1849 |
ISSN: | 1367-4811 1367-4803 |
Popis: | Motivation Alternative polyadenylation (APA) has been increasingly recognized as a crucial mechanism that contributes to transcriptome diversity and gene expression regulation. As RNA-seq has become a routine protocol for transcriptome analysis, it is of great interest to leverage such unprecedented collection of RNA-seq data by new computational methods to extract and quantify APA dynamics in these transcriptomes. However, research progress in this area has been relatively limited. Conventional methods rely on either transcript assembly to determine transcript 3′ ends or annotated poly(A) sites. Moreover, they can neither identify more than two poly(A) sites in a gene nor detect dynamic APA site usage considering more than two poly(A) sites. Results We developed an approach called APAtrap based on the mean squared error model to identify and quantify APA sites from RNA-seq data. APAtrap is capable of identifying novel 3′ UTRs and 3′ UTR extensions, which contributes to locating potential poly(A) sites in previously overlooked regions and improving genome annotations. APAtrap also aims to tally all potential poly(A) sites and detect genes with differential APA site usages between conditions. Extensive comparisons of APAtrap with two other latest methods, ChangePoint and DaPars, using various RNA-seq datasets from simulation studies, human and Arabidopsis demonstrate the efficacy and flexibility of APAtrap for any organisms with an annotated genome. Availability and implementation Freely available for download at https://apatrap.sourceforge.io. Supplementary information Supplementary data are available at Bioinformatics online. |
Databáze: | OpenAIRE |
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