Leveraging multiple transcriptome assembly methods for improved gene structure annotation

The performance of RNA-Seq aligners and assemblers varies greatly across different organisms and experiments, and often the optimal approach is not known beforehand. Here we show that the accuracy of transcript reconstruction can be boosted by combining multiple methods, and we present a novel algorithm to integrate multiple RNA-Seq assemblies into a coherent transcript annotation. Our algorithm can remove redundancies and select the best transcript models according to user-specified metrics, while solving common artefacts such as erroneous transcript chimerisms. We have implemented this method in an open-source Python3 and Cython program, Mikado, available at https://github.com/lucventurini/Mikado

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Author Venturini, Luca
Last Updated November 20, 2019, 16:51 (UTC)
Created August 1, 2019, 10:28 (UTC)
Article Host Type publisher
Article Is Open Access true
Article License Type cc-by
Article Version Type publishedVersion
Citation Report https://scite.ai/reports/10.1093/gigascience/giy09310.1101/216994
DOI 10.1093/gigascience/giy093,10.1101/216994
Date Last Updated 2019-07-11T18:25:37.207313
Evidence open (via page says license)
Funder code(s)
Journal Is Open Access true
Open Access Status gold
PDF URL https://academic.oup.com/gigascience/article-pdf/7/8/giy093/25520349/giy093.pdf
Publisher URL https://doi.org/10.1093/gigascience/giy093