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Persistent URL http://purl.org/net/epubs/work/12153231
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Record Id 12153231
Title Parallelization of the Trinity pipeline for de novo transcriptome assembly
Abstract This paper details a distributed-memory implementation of Chrysalis, part of the popular Trinity workflow used for de novo transcriptome assembly. We have implemented changes to Chrysalis, which was previously multi-threaded for shared-memory architectures, to change it to a hybrid implementation which uses both MPI and OpenMP. With the new hybrid imple- mentation, we report speedups of about a factor of twenty for both GraphFromFasta and ReadsToTranscripts on an iDataPlex cluster for a sugarbeet dataset containing around 130 million reads. Along with the hybrid implementation, we also use PyFasta to speed up Bowtie execution by a factor of three which is also part of the Trinity workflow. Overall, we reduce the runtime of the Chrysalis step of the Trinity workflow from over 50 hours to less than 5 hours for the sugarbeet dataset. By enabling the use of multi-node clusters, this implementation is a significant step towards making de novo transcriptome assembly feasible for ever bigger transcriptome datasets.
Organisation STFC , SCI-COMP
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Language English (EN)
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Paper In Conference Proceedings In 13th IEEE International Workshop on High Performance Computational Biology (HiCOMB 2014), Phoenix, Arizona, USA, 19-23 May 2014, (2014): 566-575. doi:10.1109/IPDPSW.2014.67 2014