Cargando…
Indexes of Large Genome Collections on a PC
The availability of thousands of individual genomes of one species should boost rapid progress in personalized medicine or understanding of the interaction between genotype and phenotype, to name a few applications. A key operation useful in such analyses is aligning sequencing reads against a colle...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4188820/ https://www.ncbi.nlm.nih.gov/pubmed/25289699 http://dx.doi.org/10.1371/journal.pone.0109384 |
_version_ | 1782338274620080128 |
---|---|
author | Danek, Agnieszka Deorowicz, Sebastian Grabowski, Szymon |
author_facet | Danek, Agnieszka Deorowicz, Sebastian Grabowski, Szymon |
author_sort | Danek, Agnieszka |
collection | PubMed |
description | The availability of thousands of individual genomes of one species should boost rapid progress in personalized medicine or understanding of the interaction between genotype and phenotype, to name a few applications. A key operation useful in such analyses is aligning sequencing reads against a collection of genomes, which is costly with the use of existing algorithms due to their large memory requirements. We present MuGI, Multiple Genome Index, which reports all occurrences of a given pattern, in exact and approximate matching model, against a collection of thousand(s) genomes. Its unique feature is the small index size, which is customisable. It fits in a standard computer with 16–32 GB, or even 8 GB, of RAM, for the 1000GP collection of 1092 diploid human genomes. The solution is also fast. For example, the exact matching queries (of average length 150 bp) are handled in average time of 39 µs and with up to 3 mismatches in 373 µs on the test PC with the index size of 13.4 GB. For a smaller index, occupying 7.4 GB in memory, the respective times grow to 76 µs and 917 µs. Software is available at http://sun.aei.polsl.pl/mugi under a free license. Data S1 is available at PLOS One online. |
format | Online Article Text |
id | pubmed-4188820 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-41888202014-10-10 Indexes of Large Genome Collections on a PC Danek, Agnieszka Deorowicz, Sebastian Grabowski, Szymon PLoS One Research Article The availability of thousands of individual genomes of one species should boost rapid progress in personalized medicine or understanding of the interaction between genotype and phenotype, to name a few applications. A key operation useful in such analyses is aligning sequencing reads against a collection of genomes, which is costly with the use of existing algorithms due to their large memory requirements. We present MuGI, Multiple Genome Index, which reports all occurrences of a given pattern, in exact and approximate matching model, against a collection of thousand(s) genomes. Its unique feature is the small index size, which is customisable. It fits in a standard computer with 16–32 GB, or even 8 GB, of RAM, for the 1000GP collection of 1092 diploid human genomes. The solution is also fast. For example, the exact matching queries (of average length 150 bp) are handled in average time of 39 µs and with up to 3 mismatches in 373 µs on the test PC with the index size of 13.4 GB. For a smaller index, occupying 7.4 GB in memory, the respective times grow to 76 µs and 917 µs. Software is available at http://sun.aei.polsl.pl/mugi under a free license. Data S1 is available at PLOS One online. Public Library of Science 2014-10-07 /pmc/articles/PMC4188820/ /pubmed/25289699 http://dx.doi.org/10.1371/journal.pone.0109384 Text en © 2014 Danek et al 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 Danek, Agnieszka Deorowicz, Sebastian Grabowski, Szymon Indexes of Large Genome Collections on a PC |
title | Indexes of Large Genome Collections on a PC |
title_full | Indexes of Large Genome Collections on a PC |
title_fullStr | Indexes of Large Genome Collections on a PC |
title_full_unstemmed | Indexes of Large Genome Collections on a PC |
title_short | Indexes of Large Genome Collections on a PC |
title_sort | indexes of large genome collections on a pc |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4188820/ https://www.ncbi.nlm.nih.gov/pubmed/25289699 http://dx.doi.org/10.1371/journal.pone.0109384 |
work_keys_str_mv | AT danekagnieszka indexesoflargegenomecollectionsonapc AT deorowiczsebastian indexesoflargegenomecollectionsonapc AT grabowskiszymon indexesoflargegenomecollectionsonapc |