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

Cited 2 time in Web of Science Cited 2 time in Scopus
Authors
Soe, Seokjun; Park, Yoonjae; Chae, Heejoon
Issue Date
2018-12-10
Publisher
BioMed Central
Citation
BMC Bioinformatics, 19(1):472
Keywords
DNA methylationBisulfite sequencingAlignmentApache Spark
Abstract
Background
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 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.

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/

.
ISSN
1471-2105
Language
English
URI
https://hdl.handle.net/10371/146970
DOI
https://doi.org/10.1186/s12859-018-2498-2
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College of Engineering/Engineering Practice School (공과대학/대학원)Dept. of Computer Science and Engineering (컴퓨터공학부)Journal Papers (저널논문_컴퓨터공학부)
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