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.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6105091 | PMC |
| http://dx.doi.org/10.1093/gigascience/giy093 | DOI Listing |
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