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SRComp: Short Read Sequence Compression Using Burstsort and Elias Omega Coding

Next-generation sequencing (NGS) technologies permit the rapid production of vast amounts of data at low cost. Economical data storage and transmission hence becomes an increasingly important challenge for NGS experiments. In this paper, we introduce a new non-reference based read sequence compressi...

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Detalles Bibliográficos
Autores principales: Selva, Jeremy John, Chen, Xin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3862494/
https://www.ncbi.nlm.nih.gov/pubmed/24349065
http://dx.doi.org/10.1371/journal.pone.0081414
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author Selva, Jeremy John
Chen, Xin
author_facet Selva, Jeremy John
Chen, Xin
author_sort Selva, Jeremy John
collection PubMed
description Next-generation sequencing (NGS) technologies permit the rapid production of vast amounts of data at low cost. Economical data storage and transmission hence becomes an increasingly important challenge for NGS experiments. In this paper, we introduce a new non-reference based read sequence compression tool called SRComp. It works by first employing a fast string-sorting algorithm called burstsort to sort read sequences in lexicographical order and then Elias omega-based integer coding to encode the sorted read sequences. SRComp has been benchmarked on four large NGS datasets, where experimental results show that it can run 5–35 times faster than current state-of-the-art read sequence compression tools such as BEETL and SCALCE, while retaining comparable compression efficiency for large collections of short read sequences. SRComp is a read sequence compression tool that is particularly valuable in certain applications where compression time is of major concern.
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spelling pubmed-38624942013-12-17 SRComp: Short Read Sequence Compression Using Burstsort and Elias Omega Coding Selva, Jeremy John Chen, Xin PLoS One Research Article Next-generation sequencing (NGS) technologies permit the rapid production of vast amounts of data at low cost. Economical data storage and transmission hence becomes an increasingly important challenge for NGS experiments. In this paper, we introduce a new non-reference based read sequence compression tool called SRComp. It works by first employing a fast string-sorting algorithm called burstsort to sort read sequences in lexicographical order and then Elias omega-based integer coding to encode the sorted read sequences. SRComp has been benchmarked on four large NGS datasets, where experimental results show that it can run 5–35 times faster than current state-of-the-art read sequence compression tools such as BEETL and SCALCE, while retaining comparable compression efficiency for large collections of short read sequences. SRComp is a read sequence compression tool that is particularly valuable in certain applications where compression time is of major concern. Public Library of Science 2013-12-13 /pmc/articles/PMC3862494/ /pubmed/24349065 http://dx.doi.org/10.1371/journal.pone.0081414 Text en © 2013 Selva, Chen http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Selva, Jeremy John
Chen, Xin
SRComp: Short Read Sequence Compression Using Burstsort and Elias Omega Coding
title SRComp: Short Read Sequence Compression Using Burstsort and Elias Omega Coding
title_full SRComp: Short Read Sequence Compression Using Burstsort and Elias Omega Coding
title_fullStr SRComp: Short Read Sequence Compression Using Burstsort and Elias Omega Coding
title_full_unstemmed SRComp: Short Read Sequence Compression Using Burstsort and Elias Omega Coding
title_short SRComp: Short Read Sequence Compression Using Burstsort and Elias Omega Coding
title_sort srcomp: short read sequence compression using burstsort and elias omega coding
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3862494/
https://www.ncbi.nlm.nih.gov/pubmed/24349065
http://dx.doi.org/10.1371/journal.pone.0081414
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