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

Authors
Soe, SeokjunPark, YoonjaeChae, Heejoon
Issue Date
Dec-2018
Publisher
BMC
Keywords
DNA methylation; Bisulfite sequencing; Alignment; Apache Spark
Citation
BMC BIOINFORMATICS, v.19, no.1
Journal Title
BMC BIOINFORMATICS
Volume
19
Number
1
URI
https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/4152
DOI
10.1186/s12859-018-2498-2
ISSN
1471-2105
Abstract
BackgroundBisulfite 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.ResultsIn this study, we present a highly 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.ConclusionsExperimental 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.AvailabilityThe implementation of BiSpark software package and source code is available at https://github.com/bhi-kimlab/BiSpark/.
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공과대학 (소프트웨어학부)
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