ghost-tree: creating hybrid-gene phylogenetic trees for diversity analyses View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2016-12

AUTHORS

Jennifer Fouquier, Jai Ram Rideout, Evan Bolyen, John Chase, Arron Shiffer, Daniel McDonald, Rob Knight, J Gregory Caporaso, Scott T. Kelley

ABSTRACT

BACKGROUND: Fungi play critical roles in many ecosystems, cause serious diseases in plants and animals, and pose significant threats to human health and structural integrity problems in built environments. While most fungal diversity remains unknown, the development of PCR primers for the internal transcribed spacer (ITS) combined with next-generation sequencing has substantially improved our ability to profile fungal microbial diversity. Although the high sequence variability in the ITS region facilitates more accurate species identification, it also makes multiple sequence alignment and phylogenetic analysis unreliable across evolutionarily distant fungi because the sequences are hard to align accurately. To address this issue, we created ghost-tree, a bioinformatics tool that integrates sequence data from two genetic markers into a single phylogenetic tree that can be used for diversity analyses. Our approach starts with a "foundation" phylogeny based on one genetic marker whose sequences can be aligned across organisms spanning divergent taxonomic groups (e.g., fungal families). Then, "extension" phylogenies are built for more closely related organisms (e.g., fungal species or strains) using a second more rapidly evolving genetic marker. These smaller phylogenies are then grafted onto the foundation tree by mapping taxonomic names such that each corresponding foundation-tree tip would branch into its new "extension tree" child. RESULTS: We applied ghost-tree to graft fungal extension phylogenies derived from ITS sequences onto a foundation phylogeny derived from fungal 18S sequences. Our analysis of simulated and real fungal ITS data sets found that phylogenetic distances between fungal communities computed using ghost-tree phylogenies explained significantly more variance than non-phylogenetic distances. The phylogenetic metrics also improved our ability to distinguish small differences (effect sizes) between microbial communities, though results were similar to non-phylogenetic methods for larger effect sizes. CONCLUSIONS: The Silva/UNITE-based ghost tree presented here can be easily integrated into existing fungal analysis pipelines to enhance the resolution of fungal community differences and improve understanding of these communities in built environments. The ghost-tree software package can also be used to develop phylogenetic trees for other marker gene sets that afford different taxonomic resolution, or for bridging genome trees with amplicon trees. AVAILABILITY: ghost-tree is pip-installable. All source code, documentation, and test code are available under the BSD license at https://github.com/JTFouquier/ghost-tree . More... »

PAGES

11

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s40168-016-0153-6

DOI

http://dx.doi.org/10.1186/s40168-016-0153-6

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1043819627

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/26905735


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0605", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Microbiology", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/06", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Biological Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Computational Biology", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "DNA, Intergenic", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Evolution, Molecular", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Fungi", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "High-Throughput Nucleotide Sequencing", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Microbiota", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Mutant Chimeric Proteins", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Phylogeny", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Principal Component Analysis", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Saliva", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "San Diego State University", 
          "id": "https://www.grid.ac/institutes/grid.263081.e", 
          "name": [
            "Graduate Program in Bioinformatics and Medical Informatics, San Diego State University, San Diego, CA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Fouquier", 
        "givenName": "Jennifer", 
        "id": "sg:person.0710643304.50", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0710643304.50"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Northern Arizona University", 
          "id": "https://www.grid.ac/institutes/grid.261120.6", 
          "name": [
            "Center for Microbial Genetics and Genomics, Northern Arizona University, Flagstaff, AZ, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Rideout", 
        "givenName": "Jai Ram", 
        "id": "sg:person.0741214617.83", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0741214617.83"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Northern Arizona University", 
          "id": "https://www.grid.ac/institutes/grid.261120.6", 
          "name": [
            "Center for Microbial Genetics and Genomics, Northern Arizona University, Flagstaff, AZ, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Bolyen", 
        "givenName": "Evan", 
        "id": "sg:person.07470651104.04", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07470651104.04"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Northern Arizona University", 
          "id": "https://www.grid.ac/institutes/grid.261120.6", 
          "name": [
            "Center for Microbial Genetics and Genomics, Northern Arizona University, Flagstaff, AZ, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Chase", 
        "givenName": "John", 
        "id": "sg:person.01120172040.90", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01120172040.90"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Northern Arizona University", 
          "id": "https://www.grid.ac/institutes/grid.261120.6", 
          "name": [
            "Center for Microbial Genetics and Genomics, Northern Arizona University, Flagstaff, AZ, USA", 
            "Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Shiffer", 
        "givenName": "Arron", 
        "id": "sg:person.01344041027.48", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01344041027.48"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Institute for Systems Biology", 
          "id": "https://www.grid.ac/institutes/grid.64212.33", 
          "name": [
            "Institute for Systems Biology, Seattle, WA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "McDonald", 
        "givenName": "Daniel", 
        "id": "sg:person.01324411177.44", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01324411177.44"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of California, San Diego", 
          "id": "https://www.grid.ac/institutes/grid.266100.3", 
          "name": [
            "Department of Pediatrics, and Department of Computer Science and Engineering, University of California San Diego, San Diego, CA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Knight", 
        "givenName": "Rob", 
        "id": "sg:person.016311745377.96", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016311745377.96"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Northern Arizona University", 
          "id": "https://www.grid.ac/institutes/grid.261120.6", 
          "name": [
            "Center for Microbial Genetics and Genomics, Northern Arizona University, Flagstaff, AZ, USA", 
            "Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Caporaso", 
        "givenName": "J Gregory", 
        "id": "sg:person.0624224157.70", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0624224157.70"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "San Diego State University", 
          "id": "https://www.grid.ac/institutes/grid.263081.e", 
          "name": [
            "Graduate Program in Bioinformatics and Medical Informatics, San Diego State University, San Diego, CA, USA", 
            "Department of Biology, San Diego State University, San Diego, CA, USA", 
            "San Diego State University, 5500 Campanile Drive, 92182-4614, San Diego, CA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kelley", 
        "givenName": "Scott T.", 
        "id": "sg:person.0616435110.50", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0616435110.50"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1111/j.1365-294x.1993.tb00005.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000708217"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/b978-0-12-372180-8.50042-1", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004812051"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.fbr.2010.05.001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006184966"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nmeth.f.303", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009032055", 
          "https://doi.org/10.1038/nmeth.f.303"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nmeth.f.303", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009032055", 
          "https://doi.org/10.1038/nmeth.f.303"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1128/aem.03117-14", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010269803"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/nar/gkm864", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010797283"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/b978-1-4832-3211-9.50009-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016180325"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.7717/peerj.545", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017901499"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/2047-217x-2-16", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022546943", 
          "https://doi.org/10.1186/2047-217x-2-16"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/nar/gkh340", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025846396"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature11209", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027248000", 
          "https://doi.org/10.1038/nature11209"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.femsec.2003.11.012", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028517931"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/molbev/msp077", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028540883"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/molbev/msp077", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028540883"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/23932", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032928549", 
          "https://doi.org/10.1038/23932"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/23932", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032928549", 
          "https://doi.org/10.1038/23932"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/ina.12279", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035544963"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00253-011-3800-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036118940", 
          "https://doi.org/10.1007/s00253-011-3800-7"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1128/aem.71.12.8228-8235.2005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042157769"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/mec.12481", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043063567"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1128/aem.00335-09", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043659253"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0006-3207(92)91201-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044288255"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0006-3207(92)91201-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044288255"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2307/1942268", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046249265"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1073/pnas.1117018109", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046949865"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/gb-2011-12-5-r50", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050643751", 
          "https://doi.org/10.1186/gb-2011-12-5-r50"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.ppat.1000713", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051914035"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1469-8137.1912.tb05611.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052695319"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2016-12", 
    "datePublishedReg": "2016-12-01", 
    "description": "BACKGROUND: Fungi play critical roles in many ecosystems, cause serious diseases in plants and animals, and pose significant threats to human health and structural integrity problems in built environments. While most fungal diversity remains unknown, the development of PCR primers for the internal transcribed spacer (ITS) combined with next-generation sequencing has substantially improved our ability to profile fungal microbial diversity. Although the high sequence variability in the ITS region facilitates more accurate species identification, it also makes multiple sequence alignment and phylogenetic analysis unreliable across evolutionarily distant fungi because the sequences are hard to align accurately. To address this issue, we created ghost-tree, a bioinformatics tool that integrates sequence data from two genetic markers into a single phylogenetic tree that can be used for diversity analyses. Our approach starts with a \"foundation\" phylogeny based on one genetic marker whose sequences can be aligned across organisms spanning divergent taxonomic groups (e.g., fungal families). Then, \"extension\" phylogenies are built for more closely related organisms (e.g., fungal species or strains) using a second more rapidly evolving genetic marker. These smaller phylogenies are then grafted onto the foundation tree by mapping taxonomic names such that each corresponding foundation-tree tip would branch into its new \"extension tree\" child.\nRESULTS: We applied ghost-tree to graft fungal extension phylogenies derived from ITS sequences onto a foundation phylogeny derived from fungal 18S sequences. Our analysis of simulated and real fungal ITS data sets found that phylogenetic distances between fungal communities computed using ghost-tree phylogenies explained significantly more variance than non-phylogenetic distances. The phylogenetic metrics also improved our ability to distinguish small differences (effect sizes) between microbial communities, though results were similar to non-phylogenetic methods for larger effect sizes.\nCONCLUSIONS: The Silva/UNITE-based ghost tree presented here can be easily integrated into existing fungal analysis pipelines to enhance the resolution of fungal community differences and improve understanding of these communities in built environments. The ghost-tree software package can also be used to develop phylogenetic trees for other marker gene sets that afford different taxonomic resolution, or for bridging genome trees with amplicon trees.\nAVAILABILITY: ghost-tree is pip-installable. All source code, documentation, and test code are available under the BSD license at https://github.com/JTFouquier/ghost-tree .", 
    "genre": "research_article", 
    "id": "sg:pub.10.1186/s40168-016-0153-6", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1048878", 
        "issn": [
          "2049-2618"
        ], 
        "name": "Microbiome", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "4"
      }
    ], 
    "name": "ghost-tree: creating hybrid-gene phylogenetic trees for diversity analyses", 
    "pagination": "11", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "d0bb08f445d2b3c0df96de6288685ee400ac4f2a41f56738321506fc5d91e123"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "26905735"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "101615147"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/s40168-016-0153-6"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1043819627"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/s40168-016-0153-6", 
      "https://app.dimensions.ai/details/publication/pub.1043819627"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-10T18:27", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8675_00000551.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1186%2Fs40168-016-0153-6"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/s40168-016-0153-6'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s40168-016-0153-6'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s40168-016-0153-6'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s40168-016-0153-6'


 

This table displays all metadata directly associated to this object as RDF triples.

261 TRIPLES      21 PREDICATES      65 URIs      32 LITERALS      20 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/s40168-016-0153-6 schema:about N2e13a1c5bf444427b2bcf96e73858ec2
2 N31bd1062a452447ab885185bb2f68f82
3 N4fdc167f86f64f63a291128a936c721e
4 N524c37a498704d9c83793f0216063b9d
5 Na0eb95604d384fe9973cb717b7369e4d
6 Nb16a7385ab81425aa76db4cd10a79ad6
7 Nc31e8b9d451c4d9fbf0829963a9bd36b
8 Nc8a21b6ea73944c48fe3523236facd21
9 Nef614ffa705543468d2c69cfade9664e
10 Nf28c6372e8f0456995785ac83a380834
11 Nffe7ede38e2a4922ab57478110efae4e
12 anzsrc-for:06
13 anzsrc-for:0605
14 schema:author N693946ebc5f5410ba8fb327018e80a3a
15 schema:citation sg:pub.10.1007/s00253-011-3800-7
16 sg:pub.10.1038/23932
17 sg:pub.10.1038/nature11209
18 sg:pub.10.1038/nmeth.f.303
19 sg:pub.10.1186/2047-217x-2-16
20 sg:pub.10.1186/gb-2011-12-5-r50
21 https://doi.org/10.1016/0006-3207(92)91201-3
22 https://doi.org/10.1016/b978-0-12-372180-8.50042-1
23 https://doi.org/10.1016/b978-1-4832-3211-9.50009-7
24 https://doi.org/10.1016/j.fbr.2010.05.001
25 https://doi.org/10.1016/j.femsec.2003.11.012
26 https://doi.org/10.1073/pnas.1117018109
27 https://doi.org/10.1093/molbev/msp077
28 https://doi.org/10.1093/nar/gkh340
29 https://doi.org/10.1093/nar/gkm864
30 https://doi.org/10.1111/ina.12279
31 https://doi.org/10.1111/j.1365-294x.1993.tb00005.x
32 https://doi.org/10.1111/j.1469-8137.1912.tb05611.x
33 https://doi.org/10.1111/mec.12481
34 https://doi.org/10.1128/aem.00335-09
35 https://doi.org/10.1128/aem.03117-14
36 https://doi.org/10.1128/aem.71.12.8228-8235.2005
37 https://doi.org/10.1371/journal.ppat.1000713
38 https://doi.org/10.2307/1942268
39 https://doi.org/10.7717/peerj.545
40 schema:datePublished 2016-12
41 schema:datePublishedReg 2016-12-01
42 schema:description BACKGROUND: Fungi play critical roles in many ecosystems, cause serious diseases in plants and animals, and pose significant threats to human health and structural integrity problems in built environments. While most fungal diversity remains unknown, the development of PCR primers for the internal transcribed spacer (ITS) combined with next-generation sequencing has substantially improved our ability to profile fungal microbial diversity. Although the high sequence variability in the ITS region facilitates more accurate species identification, it also makes multiple sequence alignment and phylogenetic analysis unreliable across evolutionarily distant fungi because the sequences are hard to align accurately. To address this issue, we created ghost-tree, a bioinformatics tool that integrates sequence data from two genetic markers into a single phylogenetic tree that can be used for diversity analyses. Our approach starts with a "foundation" phylogeny based on one genetic marker whose sequences can be aligned across organisms spanning divergent taxonomic groups (e.g., fungal families). Then, "extension" phylogenies are built for more closely related organisms (e.g., fungal species or strains) using a second more rapidly evolving genetic marker. These smaller phylogenies are then grafted onto the foundation tree by mapping taxonomic names such that each corresponding foundation-tree tip would branch into its new "extension tree" child. RESULTS: We applied ghost-tree to graft fungal extension phylogenies derived from ITS sequences onto a foundation phylogeny derived from fungal 18S sequences. Our analysis of simulated and real fungal ITS data sets found that phylogenetic distances between fungal communities computed using ghost-tree phylogenies explained significantly more variance than non-phylogenetic distances. The phylogenetic metrics also improved our ability to distinguish small differences (effect sizes) between microbial communities, though results were similar to non-phylogenetic methods for larger effect sizes. CONCLUSIONS: The Silva/UNITE-based ghost tree presented here can be easily integrated into existing fungal analysis pipelines to enhance the resolution of fungal community differences and improve understanding of these communities in built environments. The ghost-tree software package can also be used to develop phylogenetic trees for other marker gene sets that afford different taxonomic resolution, or for bridging genome trees with amplicon trees. AVAILABILITY: ghost-tree is pip-installable. All source code, documentation, and test code are available under the BSD license at https://github.com/JTFouquier/ghost-tree .
43 schema:genre research_article
44 schema:inLanguage en
45 schema:isAccessibleForFree true
46 schema:isPartOf N4e11fb43298b4a928467695342dea05a
47 Nbe78b1754fa94f71b5a29e3639cbb1f4
48 sg:journal.1048878
49 schema:name ghost-tree: creating hybrid-gene phylogenetic trees for diversity analyses
50 schema:pagination 11
51 schema:productId N0869ff2313f04a2ab1703a6ff175097f
52 N771c421c5ce745898a6293d99f1b9fdb
53 Na4d9c3c3c771419d8031b9ef132b7677
54 Naf5c70496cb747f08729c1302c970434
55 Ne804499b17444a858ac791eeef98a627
56 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043819627
57 https://doi.org/10.1186/s40168-016-0153-6
58 schema:sdDatePublished 2019-04-10T18:27
59 schema:sdLicense https://scigraph.springernature.com/explorer/license/
60 schema:sdPublisher N3e329ddf8b4746fcb559885946f71f36
61 schema:url http://link.springer.com/10.1186%2Fs40168-016-0153-6
62 sgo:license sg:explorer/license/
63 sgo:sdDataset articles
64 rdf:type schema:ScholarlyArticle
65 N0869ff2313f04a2ab1703a6ff175097f schema:name readcube_id
66 schema:value d0bb08f445d2b3c0df96de6288685ee400ac4f2a41f56738321506fc5d91e123
67 rdf:type schema:PropertyValue
68 N1831dd50a3194b48aa34e8f7965ec2d5 rdf:first sg:person.01120172040.90
69 rdf:rest N829da84f97094d278dc1d1a73c77eb92
70 N2d9e2517ccee443ba3916990842a415b rdf:first sg:person.016311745377.96
71 rdf:rest N65b6bc2a3e8b44dfb1c93113db1922c8
72 N2e13a1c5bf444427b2bcf96e73858ec2 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
73 schema:name Principal Component Analysis
74 rdf:type schema:DefinedTerm
75 N31bd1062a452447ab885185bb2f68f82 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
76 schema:name Saliva
77 rdf:type schema:DefinedTerm
78 N3e329ddf8b4746fcb559885946f71f36 schema:name Springer Nature - SN SciGraph project
79 rdf:type schema:Organization
80 N467d6f1e0c154bc8a20577176bb006e6 rdf:first sg:person.01324411177.44
81 rdf:rest N2d9e2517ccee443ba3916990842a415b
82 N4e11fb43298b4a928467695342dea05a schema:issueNumber 1
83 rdf:type schema:PublicationIssue
84 N4fdc167f86f64f63a291128a936c721e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
85 schema:name Fungi
86 rdf:type schema:DefinedTerm
87 N524c37a498704d9c83793f0216063b9d schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
88 schema:name Computational Biology
89 rdf:type schema:DefinedTerm
90 N5394dfe7b98b4d2c91e8fd57b22c7f35 rdf:first sg:person.07470651104.04
91 rdf:rest N1831dd50a3194b48aa34e8f7965ec2d5
92 N65b6bc2a3e8b44dfb1c93113db1922c8 rdf:first sg:person.0624224157.70
93 rdf:rest N72191cab711b4cb8aee763f533e3d59f
94 N693946ebc5f5410ba8fb327018e80a3a rdf:first sg:person.0710643304.50
95 rdf:rest Nbbf502c8c7774fccbc5b9b3992f645ca
96 N72191cab711b4cb8aee763f533e3d59f rdf:first sg:person.0616435110.50
97 rdf:rest rdf:nil
98 N771c421c5ce745898a6293d99f1b9fdb schema:name pubmed_id
99 schema:value 26905735
100 rdf:type schema:PropertyValue
101 N829da84f97094d278dc1d1a73c77eb92 rdf:first sg:person.01344041027.48
102 rdf:rest N467d6f1e0c154bc8a20577176bb006e6
103 Na0eb95604d384fe9973cb717b7369e4d schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
104 schema:name Phylogeny
105 rdf:type schema:DefinedTerm
106 Na4d9c3c3c771419d8031b9ef132b7677 schema:name nlm_unique_id
107 schema:value 101615147
108 rdf:type schema:PropertyValue
109 Naf5c70496cb747f08729c1302c970434 schema:name dimensions_id
110 schema:value pub.1043819627
111 rdf:type schema:PropertyValue
112 Nb16a7385ab81425aa76db4cd10a79ad6 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
113 schema:name Humans
114 rdf:type schema:DefinedTerm
115 Nbbf502c8c7774fccbc5b9b3992f645ca rdf:first sg:person.0741214617.83
116 rdf:rest N5394dfe7b98b4d2c91e8fd57b22c7f35
117 Nbe78b1754fa94f71b5a29e3639cbb1f4 schema:volumeNumber 4
118 rdf:type schema:PublicationVolume
119 Nc31e8b9d451c4d9fbf0829963a9bd36b schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
120 schema:name Evolution, Molecular
121 rdf:type schema:DefinedTerm
122 Nc8a21b6ea73944c48fe3523236facd21 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
123 schema:name Microbiota
124 rdf:type schema:DefinedTerm
125 Ne804499b17444a858ac791eeef98a627 schema:name doi
126 schema:value 10.1186/s40168-016-0153-6
127 rdf:type schema:PropertyValue
128 Nef614ffa705543468d2c69cfade9664e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
129 schema:name DNA, Intergenic
130 rdf:type schema:DefinedTerm
131 Nf28c6372e8f0456995785ac83a380834 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
132 schema:name Mutant Chimeric Proteins
133 rdf:type schema:DefinedTerm
134 Nffe7ede38e2a4922ab57478110efae4e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
135 schema:name High-Throughput Nucleotide Sequencing
136 rdf:type schema:DefinedTerm
137 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
138 schema:name Biological Sciences
139 rdf:type schema:DefinedTerm
140 anzsrc-for:0605 schema:inDefinedTermSet anzsrc-for:
141 schema:name Microbiology
142 rdf:type schema:DefinedTerm
143 sg:journal.1048878 schema:issn 2049-2618
144 schema:name Microbiome
145 rdf:type schema:Periodical
146 sg:person.01120172040.90 schema:affiliation https://www.grid.ac/institutes/grid.261120.6
147 schema:familyName Chase
148 schema:givenName John
149 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01120172040.90
150 rdf:type schema:Person
151 sg:person.01324411177.44 schema:affiliation https://www.grid.ac/institutes/grid.64212.33
152 schema:familyName McDonald
153 schema:givenName Daniel
154 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01324411177.44
155 rdf:type schema:Person
156 sg:person.01344041027.48 schema:affiliation https://www.grid.ac/institutes/grid.261120.6
157 schema:familyName Shiffer
158 schema:givenName Arron
159 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01344041027.48
160 rdf:type schema:Person
161 sg:person.016311745377.96 schema:affiliation https://www.grid.ac/institutes/grid.266100.3
162 schema:familyName Knight
163 schema:givenName Rob
164 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016311745377.96
165 rdf:type schema:Person
166 sg:person.0616435110.50 schema:affiliation https://www.grid.ac/institutes/grid.263081.e
167 schema:familyName Kelley
168 schema:givenName Scott T.
169 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0616435110.50
170 rdf:type schema:Person
171 sg:person.0624224157.70 schema:affiliation https://www.grid.ac/institutes/grid.261120.6
172 schema:familyName Caporaso
173 schema:givenName J Gregory
174 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0624224157.70
175 rdf:type schema:Person
176 sg:person.0710643304.50 schema:affiliation https://www.grid.ac/institutes/grid.263081.e
177 schema:familyName Fouquier
178 schema:givenName Jennifer
179 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0710643304.50
180 rdf:type schema:Person
181 sg:person.0741214617.83 schema:affiliation https://www.grid.ac/institutes/grid.261120.6
182 schema:familyName Rideout
183 schema:givenName Jai Ram
184 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0741214617.83
185 rdf:type schema:Person
186 sg:person.07470651104.04 schema:affiliation https://www.grid.ac/institutes/grid.261120.6
187 schema:familyName Bolyen
188 schema:givenName Evan
189 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07470651104.04
190 rdf:type schema:Person
191 sg:pub.10.1007/s00253-011-3800-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036118940
192 https://doi.org/10.1007/s00253-011-3800-7
193 rdf:type schema:CreativeWork
194 sg:pub.10.1038/23932 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032928549
195 https://doi.org/10.1038/23932
196 rdf:type schema:CreativeWork
197 sg:pub.10.1038/nature11209 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027248000
198 https://doi.org/10.1038/nature11209
199 rdf:type schema:CreativeWork
200 sg:pub.10.1038/nmeth.f.303 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009032055
201 https://doi.org/10.1038/nmeth.f.303
202 rdf:type schema:CreativeWork
203 sg:pub.10.1186/2047-217x-2-16 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022546943
204 https://doi.org/10.1186/2047-217x-2-16
205 rdf:type schema:CreativeWork
206 sg:pub.10.1186/gb-2011-12-5-r50 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050643751
207 https://doi.org/10.1186/gb-2011-12-5-r50
208 rdf:type schema:CreativeWork
209 https://doi.org/10.1016/0006-3207(92)91201-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044288255
210 rdf:type schema:CreativeWork
211 https://doi.org/10.1016/b978-0-12-372180-8.50042-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004812051
212 rdf:type schema:CreativeWork
213 https://doi.org/10.1016/b978-1-4832-3211-9.50009-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016180325
214 rdf:type schema:CreativeWork
215 https://doi.org/10.1016/j.fbr.2010.05.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006184966
216 rdf:type schema:CreativeWork
217 https://doi.org/10.1016/j.femsec.2003.11.012 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028517931
218 rdf:type schema:CreativeWork
219 https://doi.org/10.1073/pnas.1117018109 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046949865
220 rdf:type schema:CreativeWork
221 https://doi.org/10.1093/molbev/msp077 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028540883
222 rdf:type schema:CreativeWork
223 https://doi.org/10.1093/nar/gkh340 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025846396
224 rdf:type schema:CreativeWork
225 https://doi.org/10.1093/nar/gkm864 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010797283
226 rdf:type schema:CreativeWork
227 https://doi.org/10.1111/ina.12279 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035544963
228 rdf:type schema:CreativeWork
229 https://doi.org/10.1111/j.1365-294x.1993.tb00005.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1000708217
230 rdf:type schema:CreativeWork
231 https://doi.org/10.1111/j.1469-8137.1912.tb05611.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1052695319
232 rdf:type schema:CreativeWork
233 https://doi.org/10.1111/mec.12481 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043063567
234 rdf:type schema:CreativeWork
235 https://doi.org/10.1128/aem.00335-09 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043659253
236 rdf:type schema:CreativeWork
237 https://doi.org/10.1128/aem.03117-14 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010269803
238 rdf:type schema:CreativeWork
239 https://doi.org/10.1128/aem.71.12.8228-8235.2005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042157769
240 rdf:type schema:CreativeWork
241 https://doi.org/10.1371/journal.ppat.1000713 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051914035
242 rdf:type schema:CreativeWork
243 https://doi.org/10.2307/1942268 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046249265
244 rdf:type schema:CreativeWork
245 https://doi.org/10.7717/peerj.545 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017901499
246 rdf:type schema:CreativeWork
247 https://www.grid.ac/institutes/grid.261120.6 schema:alternateName Northern Arizona University
248 schema:name Center for Microbial Genetics and Genomics, Northern Arizona University, Flagstaff, AZ, USA
249 Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA
250 rdf:type schema:Organization
251 https://www.grid.ac/institutes/grid.263081.e schema:alternateName San Diego State University
252 schema:name Department of Biology, San Diego State University, San Diego, CA, USA
253 Graduate Program in Bioinformatics and Medical Informatics, San Diego State University, San Diego, CA, USA
254 San Diego State University, 5500 Campanile Drive, 92182-4614, San Diego, CA, USA
255 rdf:type schema:Organization
256 https://www.grid.ac/institutes/grid.266100.3 schema:alternateName University of California, San Diego
257 schema:name Department of Pediatrics, and Department of Computer Science and Engineering, University of California San Diego, San Diego, CA, USA
258 rdf:type schema:Organization
259 https://www.grid.ac/institutes/grid.64212.33 schema:alternateName Institute for Systems Biology
260 schema:name Institute for Systems Biology, Seattle, WA, USA
261 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...