BiSpark: a Spark-based highly scalable aligner for bisulfite sequencing data

Seokjun Soe, Yoonjae Park, Heejoon Chae
2018 BMC Bioinformatics  
Bisulfite sequencing is one of the major high-resolution DNA methylation measurement method. Due to the selective nucleotide conversion on unmethylated cytosines after treatment with sodium bisulfite, processing bisulfite-treated sequencing reads requires additional steps which need high computational demands. However, a dearth of efficient aligner that is designed for bisulfite-treated sequencing becomes a bottleneck of large-scale DNA methylome analyses. Results: In this study, we present a
more » ... ghly scalable, efficient, and load-balanced bisulfite aligner, BiSpark, which is designed for processing large volumes of bisulfite sequencing data. We implemented the BiSpark algorithm over the Apache Spark, a memory optimized distributed data processing framework, to achieve the maximum data parallel efficiency. The BiSpark algorithm is designed to support redistribution of imbalanced data to minimize delays on large-scale distributed environment. Conclusions: Experimental results on methylome datasets show that BiSpark significantly outperforms other state-of-the-art bisulfite sequencing aligners in terms of alignment speed and scalability with respect to dataset size and a number of computing nodes while providing highly consistent and comparable mapping results. Availability: The implementation of BiSpark software package and source code is available at https://github.com/ bhi-kimlab/BiSpark/.
doi:10.1186/s12859-018-2498-2 fatcat:fyolmxaegnds7bqiwtp4pityge