Scalable methods for analyzing and visualizing phylogenetic placement of metagenomic samples Article Swipe
Lucas Czech
,
Alexandros Stamatakis
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1371/journal.pone.0217050
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1371/journal.pone.0217050
Background: The exponential decrease in molecular sequencing cost generates unprecedented amounts of data. Hence, scalable methods to analyze these data are required. Phylogenetic (or Evolutionary) Placement methods identify the evolutionary provenance of anonymous sequences with respect to a given reference phylogeny. This increasingly popular method is deployed for scrutinizing metagenomic samples from environments such as water, soil, or the human gut. Novel methods: Here, we present novel and, more importantly, highly scalable methods for analyzing phylogenetic placements of metagenomic samples. More specifically, we introduce methods for (a) visualizing differences between samples and their correlation with associated meta-data on the reference phylogeny, (b) clustering similar samples using a variant of the k-means method, and (c) finding phylogenetic factors using an adaptation of the Phylofactorization method. These methods enable to interpret metagenomic data in a phylogenetic context, to find patterns in the data, and to identify branches of the phylogeny that are driving these patterns. Results: To demonstrate the scalability and utility of our methods, as well as to provide exemplary interpretations of our methods, we applied them to 3 publicly available datasets comprising 9782 samples with a total of approximately 168 million sequences. The results indicate that new biological insights can be attained via our methods.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1371/journal.pone.0217050
- https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0217050&type=printable
- OA Status
- gold
- Cited By
- 94
- References
- 133
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2947372214
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- OpenAlex ID
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https://openalex.org/W2947372214Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1371/journal.pone.0217050Digital Object Identifier
- Title
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Scalable methods for analyzing and visualizing phylogenetic placement of metagenomic samplesWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2019Year of publication
- Publication date
-
2019-05-28Full publication date if available
- Authors
-
Lucas Czech, Alexandros StamatakisList of authors in order
- Landing page
-
https://doi.org/10.1371/journal.pone.0217050Publisher landing page
- PDF URL
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https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0217050&type=printableDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0217050&type=printableDirect OA link when available
- Concepts
-
Phylogenetic tree, Metagenomics, Phylogenetics, Scalability, Context (archaeology), Biology, Cluster analysis, Computational biology, Computer science, Data mining, Evolutionary biology, Machine learning, Genetics, Gene, Database, PaleontologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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94Total citation count in OpenAlex
- Citations by year (recent)
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2025: 4, 2024: 7, 2023: 8, 2022: 19, 2021: 22Per-year citation counts (last 5 years)
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133Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.patterns. | 152 |
| abstract_inverted_index.phylogeny | 147 |
| abstract_inverted_index.reference | 39, 99 |
| abstract_inverted_index.required. | 21 |
| abstract_inverted_index.sequences | 33 |
| abstract_inverted_index.adaptation | 119 |
| abstract_inverted_index.associated | 95 |
| abstract_inverted_index.biological | 197 |
| abstract_inverted_index.clustering | 102 |
| abstract_inverted_index.comprising | 181 |
| abstract_inverted_index.phylogeny, | 100 |
| abstract_inverted_index.phylogeny. | 40 |
| abstract_inverted_index.placements | 76 |
| abstract_inverted_index.provenance | 30 |
| abstract_inverted_index.sequences. | 191 |
| abstract_inverted_index.sequencing | 6 |
| abstract_inverted_index.Background: | 0 |
| abstract_inverted_index.correlation | 93 |
| abstract_inverted_index.demonstrate | 155 |
| abstract_inverted_index.differences | 88 |
| abstract_inverted_index.exponential | 2 |
| abstract_inverted_index.metagenomic | 49, 78, 129 |
| abstract_inverted_index.scalability | 157 |
| abstract_inverted_index.visualizing | 87 |
| abstract_inverted_index.Phylogenetic | 22 |
| abstract_inverted_index.environments | 52 |
| abstract_inverted_index.evolutionary | 29 |
| abstract_inverted_index.importantly, | 69 |
| abstract_inverted_index.increasingly | 42 |
| abstract_inverted_index.phylogenetic | 75, 115, 133 |
| abstract_inverted_index.scrutinizing | 48 |
| abstract_inverted_index.Evolutionary) | 24 |
| abstract_inverted_index.approximately | 188 |
| abstract_inverted_index.specifically, | 81 |
| abstract_inverted_index.unprecedented | 9 |
| abstract_inverted_index.interpretations | 169 |
| abstract_inverted_index.Phylofactorization | 122 |
| cited_by_percentile_year.max | 100 |
| cited_by_percentile_year.min | 97 |
| corresponding_author_ids | https://openalex.org/A5005887668, https://openalex.org/A5025640090 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 2 |
| corresponding_institution_ids | https://openalex.org/I102335020, https://openalex.org/I71030271 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/6 |
| sustainable_development_goals[0].score | 0.75 |
| sustainable_development_goals[0].display_name | Clean water and sanitation |
| citation_normalized_percentile.value | 0.97616123 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |