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 sensitivity of the analysis can be boosted by combining multiple approaches, and we present a novel algorithm to integrate multiple RNA-Seq assemblies from different tools and technologies into a coherent transcript annotation. Our algorithm is also capable of 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.