Cargando…
Data compression for sequencing data
Post-Sanger sequencing methods produce tons of data, and there is a general agreement that the challenge to store and process them must be addressed with data compression. In this review we first answer the question “why compression” in a quantitative manner. Then we also answer the questions “what”...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3868316/ https://www.ncbi.nlm.nih.gov/pubmed/24252160 http://dx.doi.org/10.1186/1748-7188-8-25 |
_version_ | 1782296442713407488 |
---|---|
author | Deorowicz, Sebastian Grabowski, Szymon |
author_facet | Deorowicz, Sebastian Grabowski, Szymon |
author_sort | Deorowicz, Sebastian |
collection | PubMed |
description | Post-Sanger sequencing methods produce tons of data, and there is a general agreement that the challenge to store and process them must be addressed with data compression. In this review we first answer the question “why compression” in a quantitative manner. Then we also answer the questions “what” and “how”, by sketching the fundamental compression ideas, describing the main sequencing data types and formats, and comparing the specialized compression algorithms and tools. Finally, we go back to the question “why compression” and give other, perhaps surprising answers, demonstrating the pervasiveness of data compression techniques in computational biology. |
format | Online Article Text |
id | pubmed-3868316 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-38683162013-12-20 Data compression for sequencing data Deorowicz, Sebastian Grabowski, Szymon Algorithms Mol Biol Review Article Post-Sanger sequencing methods produce tons of data, and there is a general agreement that the challenge to store and process them must be addressed with data compression. In this review we first answer the question “why compression” in a quantitative manner. Then we also answer the questions “what” and “how”, by sketching the fundamental compression ideas, describing the main sequencing data types and formats, and comparing the specialized compression algorithms and tools. Finally, we go back to the question “why compression” and give other, perhaps surprising answers, demonstrating the pervasiveness of data compression techniques in computational biology. BioMed Central 2013-11-19 /pmc/articles/PMC3868316/ /pubmed/24252160 http://dx.doi.org/10.1186/1748-7188-8-25 Text en Copyright © 2013 Deorowicz and Grabowski; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Article Deorowicz, Sebastian Grabowski, Szymon Data compression for sequencing data |
title | Data compression for sequencing data |
title_full | Data compression for sequencing data |
title_fullStr | Data compression for sequencing data |
title_full_unstemmed | Data compression for sequencing data |
title_short | Data compression for sequencing data |
title_sort | data compression for sequencing data |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3868316/ https://www.ncbi.nlm.nih.gov/pubmed/24252160 http://dx.doi.org/10.1186/1748-7188-8-25 |
work_keys_str_mv | AT deorowiczsebastian datacompressionforsequencingdata AT grabowskiszymon datacompressionforsequencingdata |