A probabilistic model to recover individual genomes from metagenomes
Shotgun metagenomics of microbial communities reveal information about strains of relevance for applications in medicine, biotechnology and ecology. Recovering their genomes is a crucial but very challenging step due to the complexity of the underlying biological system and technical factors. Microb...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
PeerJ Inc.
2017-05-01
|
| Series: | PeerJ Computer Science |
| Subjects: | |
| Online Access: | https://peerj.com/articles/cs-117.pdf |
| _version_ | 1819291740256862208 |
|---|---|
| author | Johannes Dröge Alexander Schönhuth Alice C. McHardy |
| author_facet | Johannes Dröge Alexander Schönhuth Alice C. McHardy |
| author_sort | Johannes Dröge |
| collection | DOAJ |
| description | Shotgun metagenomics of microbial communities reveal information about strains of relevance for applications in medicine, biotechnology and ecology. Recovering their genomes is a crucial but very challenging step due to the complexity of the underlying biological system and technical factors. Microbial communities are heterogeneous, with oftentimes hundreds of present genomes deriving from different species or strains, all at varying abundances and with different degrees of similarity to each other and reference data. We present a versatile probabilistic model for genome recovery and analysis, which aggregates three types of information that are commonly used for genome recovery from metagenomes. As potential applications we showcase metagenome contig classification, genome sample enrichment and genome bin comparisons. The open source implementation MGLEX is available via the Python Package Index and on GitHub and can be embedded into metagenome analysis workflows and programs. |
| first_indexed | 2024-12-24T03:43:26Z |
| format | Article |
| id | doaj.art-cb83aa27d1784d97a44eaf04817e9cf0 |
| institution | Directory Open Access Journal |
| issn | 2376-5992 |
| language | English |
| last_indexed | 2024-12-24T03:43:26Z |
| publishDate | 2017-05-01 |
| publisher | PeerJ Inc. |
| record_format | Article |
| series | PeerJ Computer Science |
| spelling | doaj.art-cb83aa27d1784d97a44eaf04817e9cf02022-12-21T17:16:47ZengPeerJ Inc.PeerJ Computer Science2376-59922017-05-013e11710.7717/peerj-cs.117A probabilistic model to recover individual genomes from metagenomesJohannes Dröge0Alexander Schönhuth1Alice C. McHardy2Computational Biology of Infection Research, Helmholtz Centre for Infection Research, Braunschweig, GermanyCentrum Wiskunde & Informatica, Amsterdam, The NetherlandsComputational Biology of Infection Research, Helmholtz Centre for Infection Research, Braunschweig, GermanyShotgun metagenomics of microbial communities reveal information about strains of relevance for applications in medicine, biotechnology and ecology. Recovering their genomes is a crucial but very challenging step due to the complexity of the underlying biological system and technical factors. Microbial communities are heterogeneous, with oftentimes hundreds of present genomes deriving from different species or strains, all at varying abundances and with different degrees of similarity to each other and reference data. We present a versatile probabilistic model for genome recovery and analysis, which aggregates three types of information that are commonly used for genome recovery from metagenomes. As potential applications we showcase metagenome contig classification, genome sample enrichment and genome bin comparisons. The open source implementation MGLEX is available via the Python Package Index and on GitHub and can be embedded into metagenome analysis workflows and programs.https://peerj.com/articles/cs-117.pdfBinningMetagenomics |
| spellingShingle | Johannes Dröge Alexander Schönhuth Alice C. McHardy A probabilistic model to recover individual genomes from metagenomes PeerJ Computer Science Binning Metagenomics |
| title | A probabilistic model to recover individual genomes from metagenomes |
| title_full | A probabilistic model to recover individual genomes from metagenomes |
| title_fullStr | A probabilistic model to recover individual genomes from metagenomes |
| title_full_unstemmed | A probabilistic model to recover individual genomes from metagenomes |
| title_short | A probabilistic model to recover individual genomes from metagenomes |
| title_sort | probabilistic model to recover individual genomes from metagenomes |
| topic | Binning Metagenomics |
| url | https://peerj.com/articles/cs-117.pdf |
| work_keys_str_mv | AT johannesdroge aprobabilisticmodeltorecoverindividualgenomesfrommetagenomes AT alexanderschonhuth aprobabilisticmodeltorecoverindividualgenomesfrommetagenomes AT alicecmchardy aprobabilisticmodeltorecoverindividualgenomesfrommetagenomes AT johannesdroge probabilisticmodeltorecoverindividualgenomesfrommetagenomes AT alexanderschonhuth probabilisticmodeltorecoverindividualgenomesfrommetagenomes AT alicecmchardy probabilisticmodeltorecoverindividualgenomesfrommetagenomes |