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1.
Gigascience ; 7(8)2018 08 01.
Artículo en Inglés | MEDLINE | ID: mdl-30052957

RESUMEN

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.


Asunto(s)
Algoritmos , Perfilación de la Expresión Génica/métodos , Anotación de Secuencia Molecular/métodos , Análisis de Secuencia de ARN/métodos , Animales , Secuenciación de Nucleótidos de Alto Rendimiento/métodos , Humanos , Plantas/genética , Programas Informáticos
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