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Leveraging multiple transcriptome assembly methods for improved gene structure annotation.


ABSTRACT: Background:The performance of RNA sequencing (RNA-seq) aligners and assemblers varies greatly across different organisms and experiments, and often the optimal approach is not known beforehand. Results: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 artifacts such as erroneous transcript chimerisms. Conclusions:We have implemented this method in an open-source Python3 and Cython program, Mikado, available on GitHub.

SUBMITTER: Venturini L 

PROVIDER: S-EPMC6105091 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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Leveraging multiple transcriptome assembly methods for improved gene structure annotation.

Venturini Luca L   Caim Shabhonam S   Kaithakottil Gemy George GG   Mapleson Daniel Lee DL   Swarbreck David D  

GigaScience 20180801 8


<h4>Background</h4>The performance of RNA sequencing (RNA-seq) aligners and assemblers varies greatly across different organisms and experiments, and often the optimal approach is not known beforehand.<h4>Results</h4>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 trans  ...[more]

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