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Authors: Yuki Endo 1 ; Fubito Toyama 1 ; Chikafumi Chiba 2 ; Hiroshi Mori 1 and Kenji Shoji 1

Affiliations: 1 Utsunomiya University, Japan ; 2 University of Tsukuba, Japan

ISBN: 978-989-758-170-0

Keyword(s): Bioinfomatics, Next Generation Sequencing, de novo Assembly.

Related Ontology Subjects/Areas/Topics: Algorithms and Software Tools ; Bioinformatics ; Biomedical Engineering ; Databases and Data Management ; Genomics and Proteomics ; Next Generation Sequencing ; Sequence Analysis

Abstract: Sequencing the whole genome of various species has many applications, not only in understanding biological systems, but also in medicine, pharmacy, and agriculture. In recent years, the emergence of high-throughput next generation sequencing technologies has dramatically reduced the time and costs for whole genome sequencing. These new technologies provide ultrahigh throughput with a lower per-unit data cost. However, the data are generated from very short fragments of DNA. Thus, it is very important to develop algorithms for merging these fragments. One method of merging these fragments without using a reference dataset is called de novo assembly. Many algorithms for de novo assembly have been proposed in recent years. Velvet and SOAPdenovo2 are well-known assembly algorithms, which have good performance in terms of memory and time consumption. However, memory consumption increases dramatically when the size of input fragments is larger. Therefore, it is necessary to develop an alter native algorithm with low memory usage. In this paper, we propose an algorithm for de novo assembly with lower memory. In the proposed method, memory-efficient DSK (disk streaming of k-mers) to count k-mers is adopted. Moreover, the amount of memory usage for constructing de bruijn graph is reduced by not keeping edge information in the graph. In our experiment using human chromosome 14, the average maximum memory consumption of the proposed method was approximately 7.5–8.8% of that of the popular assemblers. (More)

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Paper citation in several formats:
Endo, Y.; Toyama, F.; Chiba, C.; Mori, H. and Shoji, K. (2016). Memory Efficient de novo Assembly Algorithm using Disk Streaming of K-mers.In Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS, (BIOSTEC 2016) ISBN 978-989-758-170-0, pages 266-271. DOI: 10.5220/0005798302660271

@conference{bioinformatics16,
author={Yuki Endo. and Fubito Toyama. and Chikafumi Chiba. and Hiroshi Mori. and Kenji Shoji.},
title={Memory Efficient de novo Assembly Algorithm using Disk Streaming of K-mers},
booktitle={Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS, (BIOSTEC 2016)},
year={2016},
pages={266-271},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005798302660271},
isbn={978-989-758-170-0},
}

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 3: BIOINFORMATICS, (BIOSTEC 2016)
TI - Memory Efficient de novo Assembly Algorithm using Disk Streaming of K-mers
SN - 978-989-758-170-0
AU - Endo, Y.
AU - Toyama, F.
AU - Chiba, C.
AU - Mori, H.
AU - Shoji, K.
PY - 2016
SP - 266
EP - 271
DO - 10.5220/0005798302660271

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