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MetaPalette: a k-mer Painting Approach for Metagenomic Taxonomic Profiling and Quantification of Novel Strain Variation

David Koslicki, Daniel Falush, Daniel Falush

mSystems, Volume: 1, Issue: 3, Start page: e00020-16

Swansea University Author: Daniel Falush

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DOI (Published version): 10.1128/msystems.00020-16

Abstract

Metagenomic profiling is challenging in part because of the highly uneven sampling of the tree of life by genome sequencing projects and the limitations imposed by performing phylogenetic inference at fixed taxonomic ranks. We present the algorithm MetaPalette, which uses long k-mer sizes (k = 30, 5...

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Published in: mSystems
ISSN: 2379-5077
Published: American Society for Microbiology 2016
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URI: https://cronfa.swan.ac.uk/Record/cronfa34179
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first_indexed 2017-07-21T15:19:22Z
last_indexed 2020-10-28T03:45:46Z
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spelling 2020-10-27T15:35:38.0018056 v2 34179 2017-06-07 MetaPalette: a k-mer Painting Approach for Metagenomic Taxonomic Profiling and Quantification of Novel Strain Variation bcbf3802c87745d80f3e94cc66a0fcbf Daniel Falush Daniel Falush true false 2017-06-07 PMSC Metagenomic profiling is challenging in part because of the highly uneven sampling of the tree of life by genome sequencing projects and the limitations imposed by performing phylogenetic inference at fixed taxonomic ranks. We present the algorithm MetaPalette, which uses long k-mer sizes (k = 30, 50) to fit a k-mer “palette” of a given sample to the k-mer palette of reference organisms. By modeling the k-mer palettes of unknown organisms, the method also gives an indication of the presence, abundance, and evolutionary relatedness of novel organisms present in the sample. The method returns a traditional, fixed-rank taxonomic profile which is shown on independently simulated data to be one of the most accurate to date. Tree figures are also returned that quantify the relatedness of novel organisms to reference sequences, and the accuracy of such figures is demonstrated on simulated spike-ins and a metagenomic soil sample. The software implementing MetaPalette is available at: https://github.com/dkoslicki/MetaPalette. Pretrained databases are included for Archaea, Bacteria, Eukaryota, and viruses. Journal Article mSystems 1 3 e00020-16 American Society for Microbiology 2379-5077 Taxonomic profiling, Metagenomics, Quantitative methods 28 6 2016 2016-06-28 10.1128/msystems.00020-16 Author Video: An author video summary of this article is available COLLEGE NANME Medicine COLLEGE CODE PMSC Swansea University RCUK, MR/M501608/1 2020-10-27T15:35:38.0018056 2017-06-07T15:02:58.2359410 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Medicine David Koslicki 1 Daniel Falush 2 Daniel Falush 3 0034179-07062017150718.pdf Falush.e00020-16.full.pdf 2017-06-07T15:07:18.0270000 Output 5408399 application/pdf Version of Record true 2017-06-07T00:00:00.0000000 Distributed under the terms of a Creative Commons CC-BY License. true eng
title MetaPalette: a k-mer Painting Approach for Metagenomic Taxonomic Profiling and Quantification of Novel Strain Variation
spellingShingle MetaPalette: a k-mer Painting Approach for Metagenomic Taxonomic Profiling and Quantification of Novel Strain Variation
Daniel Falush
title_short MetaPalette: a k-mer Painting Approach for Metagenomic Taxonomic Profiling and Quantification of Novel Strain Variation
title_full MetaPalette: a k-mer Painting Approach for Metagenomic Taxonomic Profiling and Quantification of Novel Strain Variation
title_fullStr MetaPalette: a k-mer Painting Approach for Metagenomic Taxonomic Profiling and Quantification of Novel Strain Variation
title_full_unstemmed MetaPalette: a k-mer Painting Approach for Metagenomic Taxonomic Profiling and Quantification of Novel Strain Variation
title_sort MetaPalette: a k-mer Painting Approach for Metagenomic Taxonomic Profiling and Quantification of Novel Strain Variation
author_id_str_mv bcbf3802c87745d80f3e94cc66a0fcbf
author_id_fullname_str_mv bcbf3802c87745d80f3e94cc66a0fcbf_***_Daniel Falush
author Daniel Falush
author2 David Koslicki
Daniel Falush
Daniel Falush
format Journal article
container_title mSystems
container_volume 1
container_issue 3
container_start_page e00020-16
publishDate 2016
institution Swansea University
issn 2379-5077
doi_str_mv 10.1128/msystems.00020-16
publisher American Society for Microbiology
college_str Faculty of Medicine, Health and Life Sciences
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hierarchy_top_id facultyofmedicinehealthandlifesciences
hierarchy_top_title Faculty of Medicine, Health and Life Sciences
hierarchy_parent_id facultyofmedicinehealthandlifesciences
hierarchy_parent_title Faculty of Medicine, Health and Life Sciences
department_str Swansea University Medical School - Medicine{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Medicine
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description Metagenomic profiling is challenging in part because of the highly uneven sampling of the tree of life by genome sequencing projects and the limitations imposed by performing phylogenetic inference at fixed taxonomic ranks. We present the algorithm MetaPalette, which uses long k-mer sizes (k = 30, 50) to fit a k-mer “palette” of a given sample to the k-mer palette of reference organisms. By modeling the k-mer palettes of unknown organisms, the method also gives an indication of the presence, abundance, and evolutionary relatedness of novel organisms present in the sample. The method returns a traditional, fixed-rank taxonomic profile which is shown on independently simulated data to be one of the most accurate to date. Tree figures are also returned that quantify the relatedness of novel organisms to reference sequences, and the accuracy of such figures is demonstrated on simulated spike-ins and a metagenomic soil sample. The software implementing MetaPalette is available at: https://github.com/dkoslicki/MetaPalette. Pretrained databases are included for Archaea, Bacteria, Eukaryota, and viruses.
published_date 2016-06-28T03:42:23Z
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score 11.037603

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