2 Search Results for "Rahman, Amatur"

Document
DOI: 10.4230/LIPIcs.WABI.2023.17
Compression Algorithm for Colored de Bruijn Graphs

Authors: Amatur Rahman, Yoann Dufresne, and Paul Medvedev

Published in: LIPIcs, Volume 273, 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)

Abstract
A colored de Bruijn graph (also called a set of k-mer sets), is a set of k-mers with every k-mer assigned a set of colors. Colored de Bruijn graphs are used in a variety of applications, including variant calling, genome assembly, and database search. However, their size has posed a scalability challenge to algorithm developers and users. There have been numerous indexing data structures proposed that allow to store the graph compactly while supporting fast query operations. However, disk compression algorithms, which do not need to support queries on the compressed data and can thus be more space-efficient, have received little attention. The dearth of specialized compression tools has been a detriment to tool developers, tool users, and reproducibility efforts. In this paper, we develop a new tool that compresses colored de Bruijn graphs to disk, building on previous ideas for compression of k-mer sets and indexing colored de Bruijn graphs. We test our tool, called ESS-color, on various datasets, including both sequencing data and whole genomes. ESS-color achieves better compression than all evaluated tools and all datasets, with no other tool able to consistently achieve less than 44% space overhead.
Cite as

Amatur Rahman, Yoann Dufresne, and Paul Medvedev. Compression Algorithm for Colored de Bruijn Graphs. In 23rd International Workshop on Algorithms in Bioinformatics (WABI 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 273, pp. 17:1-17:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{rahman_et_al:LIPIcs.WABI.2023.17,
  author =	{Rahman, Amatur and Dufresne, Yoann and Medvedev, Paul},
  title =	{{Compression Algorithm for Colored de Bruijn Graphs}},
  booktitle =	{23rd International Workshop on Algorithms in Bioinformatics (WABI 2023)},
  pages =	{17:1--17:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-294-5},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{273},
  editor =	{Belazzougui, Djamal and Ouangraoua, A\"{i}da},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2023.17},
  URN =		{urn:nbn:de:0030-drops-186434},
  doi =		{10.4230/LIPIcs.WABI.2023.17},
  annote =	{Keywords: colored de Bruijn graphs, disk compression, k-mer sets, simplitigs, spectrum-preserving string sets}
}
Document
DOI: 10.4230/LIPIcs.WABI.2020.16
Disk Compression of k-mer Sets

Authors: Amatur Rahman, Rayan Chikhi, and Paul Medvedev

Published in: LIPIcs, Volume 172, 20th International Workshop on Algorithms in Bioinformatics (WABI 2020)

Abstract
K-mer based methods have become prevalent in many areas of bioinformatics. In applications such as database search, they often work with large multi-terabyte-sized datasets. Storing such large datasets is a detriment to tool developers, tool users, and reproducibility efforts. General purpose compressors like gzip, or those designed for read data, are sub-optimal because they do not take into account the specific redundancy pattern in k-mer sets. In our earlier work (Rahman and Medvedev, RECOMB 2020), we presented an algorithm UST-Compress that uses a spectrum-preserving string set representation to compress a set of k-mers to disk. In this paper, we present two improved methods for disk compression of k-mer sets, called ESS-Compress and ESS-Tip-Compress. They use a more relaxed notion of string set representation to further remove redundancy from the representation of UST-Compress. We explore their behavior both theoretically and on real data. We show that they improve the compression sizes achieved by UST-Compress by up to 27 percent, across a breadth of datasets. We also derive lower bounds on how well this type of compression strategy can hope to do.
Cite as

Amatur Rahman, Rayan Chikhi, and Paul Medvedev. Disk Compression of k-mer Sets. In 20th International Workshop on Algorithms in Bioinformatics (WABI 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 172, pp. 16:1-16:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

Copy BibTex To Clipboard

@InProceedings{rahman_et_al:LIPIcs.WABI.2020.16,
  author =	{Rahman, Amatur and Chikhi, Rayan and Medvedev, Paul},
  title =	{{Disk Compression of k-mer Sets}},
  booktitle =	{20th International Workshop on Algorithms in Bioinformatics (WABI 2020)},
  pages =	{16:1--16:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-161-0},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{172},
  editor =	{Kingsford, Carl and Pisanti, Nadia},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2020.16},
  URN =		{urn:nbn:de:0030-drops-128057},
  doi =		{10.4230/LIPIcs.WABI.2020.16},
  annote =	{Keywords: de Bruijn graphs, compression, k-mer sets, spectrum-preserving string sets}
}
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