Correlation detection strategies in microbial data sets vary widely in sensitivity and precision View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2016-02-23

AUTHORS

Sophie Weiss, Will Van Treuren, Catherine Lozupone, Karoline Faust, Jonathan Friedman, Ye Deng, Li Charlie Xia, Zhenjiang Zech Xu, Luke Ursell, Eric J Alm, Amanda Birmingham, Jacob A Cram, Jed A Fuhrman, Jeroen Raes, Fengzhu Sun, Jizhong Zhou, Rob Knight

ABSTRACT

Disruption of healthy microbial communities has been linked to numerous diseases, yet microbial interactions are little understood. This is due in part to the large number of bacteria, and the much larger number of interactions (easily in the millions), making experimental investigation very difficult at best and necessitating the nascent field of computational exploration through microbial correlation networks. We benchmark the performance of eight correlation techniques on simulated and real data in response to challenges specific to microbiome studies: fractional sampling of ribosomal RNA sequences, uneven sampling depths, rare microbes and a high proportion of zero counts. Also tested is the ability to distinguish signals from noise, and detect a range of ecological and time-series relationships. Finally, we provide specific recommendations for correlation technique usage. Although some methods perform better than others, there is still considerable need for improvement in current techniques. More... »

PAGES

1669-1681

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/ismej.2015.235

DOI

http://dx.doi.org/10.1038/ismej.2015.235

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1024596109

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/26905627


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/2008/06", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Biological Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "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"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Bacteria", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Benchmarking", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Computational Biology", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Microbial Interactions", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Microbiota", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Models, Statistical", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "RNA, Ribosomal, 16S", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Statistics as Topic", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Department of Chemical and Biological Engineering, University of Colorado at Boulder, Boulder, CO, USA", 
          "id": "http://www.grid.ac/institutes/grid.266190.a", 
          "name": [
            "Department of Chemical and Biological Engineering, University of Colorado at Boulder, Boulder, CO, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Weiss", 
        "givenName": "Sophie", 
        "id": "sg:person.01166324530.84", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01166324530.84"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "BioFrontiers Institute, University of Colorado at Boulder, Boulder, CO, USA", 
          "id": "http://www.grid.ac/institutes/grid.266190.a", 
          "name": [
            "BioFrontiers Institute, University of Colorado at Boulder, Boulder, CO, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Van Treuren", 
        "givenName": "Will", 
        "id": "sg:person.01123102026.79", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01123102026.79"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Medicine, University of Colorado, Denver, CO, USA", 
          "id": "http://www.grid.ac/institutes/grid.241116.1", 
          "name": [
            "Department of Medicine, University of Colorado, Denver, CO, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Lozupone", 
        "givenName": "Catherine", 
        "id": "sg:person.0672337357.81", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0672337357.81"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Laboratory of Microbiology, Vrije Universiteit Brussel, Brussels, Belgium", 
          "id": "http://www.grid.ac/institutes/grid.8767.e", 
          "name": [
            "Department of Microbiology and Immunology, Rega Institute KU Leuven, Leuven, Belgium", 
            "VIB Center for the Biology of Disease, VIB, Leuven, Belgium", 
            "Laboratory of Microbiology, Vrije Universiteit Brussel, Brussels, Belgium"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Faust", 
        "givenName": "Karoline", 
        "id": "sg:person.01054521721.78", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01054521721.78"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Physics, Massachusetts Institute of Technology, Cambridge, MA, USA", 
          "id": "http://www.grid.ac/institutes/grid.116068.8", 
          "name": [
            "Department of Physics, Massachusetts Institute of Technology, Cambridge, MA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Friedman", 
        "givenName": "Jonathan", 
        "id": "sg:person.0670257026.89", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0670257026.89"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK, USA", 
          "id": "http://www.grid.ac/institutes/grid.266900.b", 
          "name": [
            "CAS Key Laboratory of Environmental Biotechnology, Chinese Academy of Sciences, Beijing, China", 
            "Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Deng", 
        "givenName": "Ye", 
        "id": "sg:person.01136447106.13", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01136447106.13"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Statistics, The Wharton School, University of Pennsylvania, Philadelphia, PA, USA", 
          "id": "http://www.grid.ac/institutes/grid.25879.31", 
          "name": [
            "Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA", 
            "Department of Statistics, The Wharton School, University of Pennsylvania, Philadelphia, PA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Xia", 
        "givenName": "Li Charlie", 
        "id": "sg:person.01267011446.28", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01267011446.28"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Departments of Pediatrics, University of California San Diego, La Jolla, CA, USA", 
          "id": "http://www.grid.ac/institutes/grid.266100.3", 
          "name": [
            "Departments of Pediatrics, University of California San Diego, La Jolla, CA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Xu", 
        "givenName": "Zhenjiang Zech", 
        "id": "sg:person.01161573701.69", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01161573701.69"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Biota Technology, Inc., Denver, CO, USA", 
          "id": "http://www.grid.ac/institutes/None", 
          "name": [
            "Biota Technology, Inc., Denver, CO, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ursell", 
        "givenName": "Luke", 
        "id": "sg:person.0624766217.74", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0624766217.74"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Biological Engineering, Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, MA, USA", 
          "id": "http://www.grid.ac/institutes/grid.116068.8", 
          "name": [
            "Department of Biological Engineering, Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, MA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Alm", 
        "givenName": "Eric J", 
        "id": "sg:person.0622302463.69", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0622302463.69"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Medicine, Center for Computational Biology and Bioinformatics, University of California San Diego, La Jolla, CA, USA", 
          "id": "http://www.grid.ac/institutes/grid.266100.3", 
          "name": [
            "Department of Medicine, Center for Computational Biology and Bioinformatics, University of California San Diego, La Jolla, CA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Birmingham", 
        "givenName": "Amanda", 
        "id": "sg:person.01231155371.50", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01231155371.50"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Biological Sciences, University of Southern California, Los Angeles, CA, USA", 
          "id": "http://www.grid.ac/institutes/grid.42505.36", 
          "name": [
            "Department of Biological Sciences, University of Southern California, Los Angeles, CA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Cram", 
        "givenName": "Jacob A", 
        "id": "sg:person.0657633746.30", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0657633746.30"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Biological Sciences, University of Southern California, Los Angeles, CA, USA", 
          "id": "http://www.grid.ac/institutes/grid.42505.36", 
          "name": [
            "Department of Biological Sciences, University of Southern California, Los Angeles, CA, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Fuhrman", 
        "givenName": "Jed A", 
        "id": "sg:person.0725061453.51", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0725061453.51"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Laboratory of Microbiology, Vrije Universiteit Brussel, Brussels, Belgium", 
          "id": "http://www.grid.ac/institutes/grid.8767.e", 
          "name": [
            "Department of Microbiology and Immunology, Rega Institute KU Leuven, Leuven, Belgium", 
            "VIB Center for the Biology of Disease, VIB, Leuven, Belgium", 
            "Laboratory of Microbiology, Vrije Universiteit Brussel, Brussels, Belgium"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Raes", 
        "givenName": "Jeroen", 
        "id": "sg:person.0765515705.86", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0765515705.86"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Molecular and Computational Biology Program, University of Southern California, Los Angeles, California, USA", 
          "id": "http://www.grid.ac/institutes/grid.42505.36", 
          "name": [
            "Molecular and Computational Biology Program, University of Southern California, Los Angeles, California, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Sun", 
        "givenName": "Fengzhu", 
        "id": "sg:person.0637727227.25", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0637727227.25"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China", 
          "id": "http://www.grid.ac/institutes/grid.12527.33", 
          "name": [
            "Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK, USA", 
            "Earth Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA", 
            "State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zhou", 
        "givenName": "Jizhong", 
        "id": "sg:person.01171352100.63", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01171352100.63"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA", 
          "id": "http://www.grid.ac/institutes/grid.266100.3", 
          "name": [
            "Departments of Pediatrics, University of California San Diego, La Jolla, CA, USA", 
            "Department of Computer Science and Engineering, University of California San Diego, La Jolla, 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"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1038/nmeth.2658", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002139060", 
          "https://doi.org/10.1038/nmeth.2658"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/1471-2105-13-113", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032970670", 
          "https://doi.org/10.1186/1471-2105-13-113"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature09922", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043309820", 
          "https://doi.org/10.1038/nature09922"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/ismej.2013.54", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023249054", 
          "https://doi.org/10.1038/ismej.2013.54"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-94-009-4109-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1109716595", 
          "https://doi.org/10.1007/978-94-009-4109-0"
        ], 
        "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": "sg:pub.10.1038/nature09944", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026204536", 
          "https://doi.org/10.1038/nature09944"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/ismej.2011.24", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007074967", 
          "https://doi.org/10.1038/ismej.2011.24"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature07540", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030170002", 
          "https://doi.org/10.1038/nature07540"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nrmicro2832", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030236624", 
          "https://doi.org/10.1038/nrmicro2832"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/gb-2010-11-10-r106", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031289083", 
          "https://doi.org/10.1186/gb-2010-11-10-r106"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/ismej.2010.204", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031320129", 
          "https://doi.org/10.1038/ismej.2010.204"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature13828", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004780748", 
          "https://doi.org/10.1038/nature13828"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2016-02-23", 
    "datePublishedReg": "2016-02-23", 
    "description": "Disruption of healthy microbial communities has been linked to numerous diseases, yet microbial interactions are little understood. This is due in part to the large number of bacteria, and the much larger number of interactions (easily in the millions), making experimental investigation very difficult at best and necessitating the nascent field of computational exploration through microbial correlation networks. We benchmark the performance of eight correlation techniques on simulated and real data in response to challenges specific to microbiome studies: fractional sampling of ribosomal RNA sequences, uneven sampling depths, rare microbes and a high proportion of zero counts. Also tested is the ability to distinguish signals from noise, and detect a range of ecological and time-series relationships. Finally, we provide specific recommendations for correlation technique usage. Although some methods perform better than others, there is still considerable need for improvement in current techniques.", 
    "genre": "article", 
    "id": "sg:pub.10.1038/ismej.2015.235", 
    "inLanguage": "en", 
    "isAccessibleForFree": true, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.3130003", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.2529347", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.2691272", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1038436", 
        "issn": [
          "1751-7362", 
          "1751-7370"
        ], 
        "name": "The ISME Journal: Multidisciplinary Journal of Microbial Ecology", 
        "publisher": "Springer Nature", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "7", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "10"
      }
    ], 
    "keywords": [
      "microbial correlation networks", 
      "ribosomal RNA sequences", 
      "healthy microbial community", 
      "microbial data sets", 
      "rare microbes", 
      "microbial interactions", 
      "microbial communities", 
      "RNA sequences", 
      "microbiome studies", 
      "numerous diseases", 
      "correlation network", 
      "large number", 
      "microbes", 
      "nascent field", 
      "bacteria", 
      "sequence", 
      "interaction", 
      "higher proportion", 
      "disruption", 
      "computational exploration", 
      "community", 
      "number", 
      "data sets", 
      "response", 
      "ability", 
      "signals", 
      "proportion", 
      "disease", 
      "sampling", 
      "strategies", 
      "part", 
      "current techniques", 
      "relationship", 
      "study", 
      "detection strategy", 
      "time-series relationship", 
      "sensitivity", 
      "real data", 
      "data", 
      "range", 
      "set", 
      "investigation", 
      "network", 
      "count", 
      "depth", 
      "considerable need", 
      "technique usage", 
      "exploration", 
      "challenges", 
      "technique", 
      "field", 
      "usage", 
      "correlation technique", 
      "fractional sampling", 
      "need", 
      "method", 
      "performance", 
      "precision", 
      "noise", 
      "improvement", 
      "recommendations", 
      "specific recommendations", 
      "experimental investigation", 
      "correlation technique usage", 
      "Correlation detection strategies"
    ], 
    "name": "Correlation detection strategies in microbial data sets vary widely in sensitivity and precision", 
    "pagination": "1669-1681", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1024596109"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1038/ismej.2015.235"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "26905627"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1038/ismej.2015.235", 
      "https://app.dimensions.ai/details/publication/pub.1024596109"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2022-01-01T18:39", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20220101/entities/gbq_results/article/article_696.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://doi.org/10.1038/ismej.2015.235"
  }
]
 

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.10.1038/ismej.2015.235'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/ismej.2015.235'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/ismej.2015.235'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/ismej.2015.235'


 

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

376 TRIPLES      22 PREDICATES      113 URIs      92 LITERALS      16 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1038/ismej.2015.235 schema:about N2aa79323b71f4f5ea6ac0a6bb555a260
2 N2c88cb8ffb5f4c3c8613ea54c8c66257
3 N3c7447ff5299481dbce508abbbd6e832
4 N5771ff8afa844b9da85df860f1b2d3ae
5 N82c6e65bac1045c880f6325b21a8c4cd
6 N9c839a8f8e684be2b779c20d49a4dccc
7 Nbfe45440190748f29b59cea176046ef6
8 Nc1da88e4312e4104b4f7fe9fec39774d
9 Neeec0962a04a49ed85eb0cd8e9562cc7
10 anzsrc-for:06
11 anzsrc-for:0605
12 schema:author N939194406e3b4581b62a075d0bff9098
13 schema:citation sg:pub.10.1007/978-94-009-4109-0
14 sg:pub.10.1038/ismej.2010.204
15 sg:pub.10.1038/ismej.2011.24
16 sg:pub.10.1038/ismej.2013.54
17 sg:pub.10.1038/nature07540
18 sg:pub.10.1038/nature09922
19 sg:pub.10.1038/nature09944
20 sg:pub.10.1038/nature13828
21 sg:pub.10.1038/nmeth.2658
22 sg:pub.10.1038/nrmicro2832
23 sg:pub.10.1186/1471-2105-13-113
24 sg:pub.10.1186/gb-2010-11-10-r106
25 sg:pub.10.1186/gb-2011-12-5-r50
26 schema:datePublished 2016-02-23
27 schema:datePublishedReg 2016-02-23
28 schema:description Disruption of healthy microbial communities has been linked to numerous diseases, yet microbial interactions are little understood. This is due in part to the large number of bacteria, and the much larger number of interactions (easily in the millions), making experimental investigation very difficult at best and necessitating the nascent field of computational exploration through microbial correlation networks. We benchmark the performance of eight correlation techniques on simulated and real data in response to challenges specific to microbiome studies: fractional sampling of ribosomal RNA sequences, uneven sampling depths, rare microbes and a high proportion of zero counts. Also tested is the ability to distinguish signals from noise, and detect a range of ecological and time-series relationships. Finally, we provide specific recommendations for correlation technique usage. Although some methods perform better than others, there is still considerable need for improvement in current techniques.
29 schema:genre article
30 schema:inLanguage en
31 schema:isAccessibleForFree true
32 schema:isPartOf N68cfdfd4639f4aceb39c8a09295e486a
33 Ncc86cd3ead514fa59e792e7dcf32a989
34 sg:journal.1038436
35 schema:keywords Correlation detection strategies
36 RNA sequences
37 ability
38 bacteria
39 challenges
40 community
41 computational exploration
42 considerable need
43 correlation network
44 correlation technique
45 correlation technique usage
46 count
47 current techniques
48 data
49 data sets
50 depth
51 detection strategy
52 disease
53 disruption
54 experimental investigation
55 exploration
56 field
57 fractional sampling
58 healthy microbial community
59 higher proportion
60 improvement
61 interaction
62 investigation
63 large number
64 method
65 microbes
66 microbial communities
67 microbial correlation networks
68 microbial data sets
69 microbial interactions
70 microbiome studies
71 nascent field
72 need
73 network
74 noise
75 number
76 numerous diseases
77 part
78 performance
79 precision
80 proportion
81 range
82 rare microbes
83 real data
84 recommendations
85 relationship
86 response
87 ribosomal RNA sequences
88 sampling
89 sensitivity
90 sequence
91 set
92 signals
93 specific recommendations
94 strategies
95 study
96 technique
97 technique usage
98 time-series relationship
99 usage
100 schema:name Correlation detection strategies in microbial data sets vary widely in sensitivity and precision
101 schema:pagination 1669-1681
102 schema:productId N10b592ddf148468b892e54a9bf36d237
103 N2a7c2769266d42a8966aea2b69fe4468
104 N7efa4a45783b47de93749b205ecab445
105 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024596109
106 https://doi.org/10.1038/ismej.2015.235
107 schema:sdDatePublished 2022-01-01T18:39
108 schema:sdLicense https://scigraph.springernature.com/explorer/license/
109 schema:sdPublisher N7e6c82b98f2f4472855cab1ed755c768
110 schema:url https://doi.org/10.1038/ismej.2015.235
111 sgo:license sg:explorer/license/
112 sgo:sdDataset articles
113 rdf:type schema:ScholarlyArticle
114 N05994292ad8c405596b2709889f66130 rdf:first sg:person.01136447106.13
115 rdf:rest Nfa94573ead15401390eff912cd7dc77d
116 N10b592ddf148468b892e54a9bf36d237 schema:name pubmed_id
117 schema:value 26905627
118 rdf:type schema:PropertyValue
119 N166bc096a8ed40ca8fcce83ea638cee1 rdf:first sg:person.0670257026.89
120 rdf:rest N05994292ad8c405596b2709889f66130
121 N2a7c2769266d42a8966aea2b69fe4468 schema:name dimensions_id
122 schema:value pub.1024596109
123 rdf:type schema:PropertyValue
124 N2aa79323b71f4f5ea6ac0a6bb555a260 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
125 schema:name Statistics as Topic
126 rdf:type schema:DefinedTerm
127 N2c88cb8ffb5f4c3c8613ea54c8c66257 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
128 schema:name Microbiota
129 rdf:type schema:DefinedTerm
130 N33a3b7a647b84013be8491bd2152df2a rdf:first sg:person.016311745377.96
131 rdf:rest rdf:nil
132 N3c7447ff5299481dbce508abbbd6e832 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
133 schema:name Computational Biology
134 rdf:type schema:DefinedTerm
135 N49075254ac0d4908a8333e75216f61da rdf:first sg:person.01161573701.69
136 rdf:rest Nee800cccf0e344558aab06bbebee5e71
137 N5771ff8afa844b9da85df860f1b2d3ae schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
138 schema:name Benchmarking
139 rdf:type schema:DefinedTerm
140 N6663e94c671f413b8a693ebeb86e18c0 rdf:first sg:person.0637727227.25
141 rdf:rest Nbdd093db032d4709b1551804ca4c44f5
142 N68cfdfd4639f4aceb39c8a09295e486a schema:issueNumber 7
143 rdf:type schema:PublicationIssue
144 N6ca589d941a642279faf120bbfe6587a rdf:first sg:person.01054521721.78
145 rdf:rest N166bc096a8ed40ca8fcce83ea638cee1
146 N7e6c82b98f2f4472855cab1ed755c768 schema:name Springer Nature - SN SciGraph project
147 rdf:type schema:Organization
148 N7efa4a45783b47de93749b205ecab445 schema:name doi
149 schema:value 10.1038/ismej.2015.235
150 rdf:type schema:PropertyValue
151 N82c6e65bac1045c880f6325b21a8c4cd schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
152 schema:name Models, Statistical
153 rdf:type schema:DefinedTerm
154 N92f6ca54ab864999b74575344f30d373 rdf:first sg:person.0622302463.69
155 rdf:rest Ncac2793b760745868ca5c171dcb8a7b7
156 N939194406e3b4581b62a075d0bff9098 rdf:first sg:person.01166324530.84
157 rdf:rest Ne51db17a29e345fdb6397487248c7c8f
158 N9c839a8f8e684be2b779c20d49a4dccc schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
159 schema:name RNA, Ribosomal, 16S
160 rdf:type schema:DefinedTerm
161 Na8dd1055b74b4ca5af9dcf7c9baeafcf rdf:first sg:person.0657633746.30
162 rdf:rest Ncba74a4934904f67bee610e1fa95a067
163 Naa6de7612eeb4cf8b2f09abf19e6ea20 rdf:first sg:person.0672337357.81
164 rdf:rest N6ca589d941a642279faf120bbfe6587a
165 Nbdd093db032d4709b1551804ca4c44f5 rdf:first sg:person.01171352100.63
166 rdf:rest N33a3b7a647b84013be8491bd2152df2a
167 Nbfe45440190748f29b59cea176046ef6 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
168 schema:name Humans
169 rdf:type schema:DefinedTerm
170 Nc0c227a7e4424145b8368ceee648f35a rdf:first sg:person.0765515705.86
171 rdf:rest N6663e94c671f413b8a693ebeb86e18c0
172 Nc1da88e4312e4104b4f7fe9fec39774d schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
173 schema:name Bacteria
174 rdf:type schema:DefinedTerm
175 Ncac2793b760745868ca5c171dcb8a7b7 rdf:first sg:person.01231155371.50
176 rdf:rest Na8dd1055b74b4ca5af9dcf7c9baeafcf
177 Ncba74a4934904f67bee610e1fa95a067 rdf:first sg:person.0725061453.51
178 rdf:rest Nc0c227a7e4424145b8368ceee648f35a
179 Ncc86cd3ead514fa59e792e7dcf32a989 schema:volumeNumber 10
180 rdf:type schema:PublicationVolume
181 Ne51db17a29e345fdb6397487248c7c8f rdf:first sg:person.01123102026.79
182 rdf:rest Naa6de7612eeb4cf8b2f09abf19e6ea20
183 Nee800cccf0e344558aab06bbebee5e71 rdf:first sg:person.0624766217.74
184 rdf:rest N92f6ca54ab864999b74575344f30d373
185 Neeec0962a04a49ed85eb0cd8e9562cc7 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
186 schema:name Microbial Interactions
187 rdf:type schema:DefinedTerm
188 Nfa94573ead15401390eff912cd7dc77d rdf:first sg:person.01267011446.28
189 rdf:rest N49075254ac0d4908a8333e75216f61da
190 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
191 schema:name Biological Sciences
192 rdf:type schema:DefinedTerm
193 anzsrc-for:0605 schema:inDefinedTermSet anzsrc-for:
194 schema:name Microbiology
195 rdf:type schema:DefinedTerm
196 sg:grant.2529347 http://pending.schema.org/fundedItem sg:pub.10.1038/ismej.2015.235
197 rdf:type schema:MonetaryGrant
198 sg:grant.2691272 http://pending.schema.org/fundedItem sg:pub.10.1038/ismej.2015.235
199 rdf:type schema:MonetaryGrant
200 sg:grant.3130003 http://pending.schema.org/fundedItem sg:pub.10.1038/ismej.2015.235
201 rdf:type schema:MonetaryGrant
202 sg:journal.1038436 schema:issn 1751-7362
203 1751-7370
204 schema:name The ISME Journal: Multidisciplinary Journal of Microbial Ecology
205 schema:publisher Springer Nature
206 rdf:type schema:Periodical
207 sg:person.01054521721.78 schema:affiliation grid-institutes:grid.8767.e
208 schema:familyName Faust
209 schema:givenName Karoline
210 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01054521721.78
211 rdf:type schema:Person
212 sg:person.01123102026.79 schema:affiliation grid-institutes:grid.266190.a
213 schema:familyName Van Treuren
214 schema:givenName Will
215 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01123102026.79
216 rdf:type schema:Person
217 sg:person.01136447106.13 schema:affiliation grid-institutes:grid.266900.b
218 schema:familyName Deng
219 schema:givenName Ye
220 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01136447106.13
221 rdf:type schema:Person
222 sg:person.01161573701.69 schema:affiliation grid-institutes:grid.266100.3
223 schema:familyName Xu
224 schema:givenName Zhenjiang Zech
225 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01161573701.69
226 rdf:type schema:Person
227 sg:person.01166324530.84 schema:affiliation grid-institutes:grid.266190.a
228 schema:familyName Weiss
229 schema:givenName Sophie
230 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01166324530.84
231 rdf:type schema:Person
232 sg:person.01171352100.63 schema:affiliation grid-institutes:grid.12527.33
233 schema:familyName Zhou
234 schema:givenName Jizhong
235 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01171352100.63
236 rdf:type schema:Person
237 sg:person.01231155371.50 schema:affiliation grid-institutes:grid.266100.3
238 schema:familyName Birmingham
239 schema:givenName Amanda
240 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01231155371.50
241 rdf:type schema:Person
242 sg:person.01267011446.28 schema:affiliation grid-institutes:grid.25879.31
243 schema:familyName Xia
244 schema:givenName Li Charlie
245 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01267011446.28
246 rdf:type schema:Person
247 sg:person.016311745377.96 schema:affiliation grid-institutes:grid.266100.3
248 schema:familyName Knight
249 schema:givenName Rob
250 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016311745377.96
251 rdf:type schema:Person
252 sg:person.0622302463.69 schema:affiliation grid-institutes:grid.116068.8
253 schema:familyName Alm
254 schema:givenName Eric J
255 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0622302463.69
256 rdf:type schema:Person
257 sg:person.0624766217.74 schema:affiliation grid-institutes:None
258 schema:familyName Ursell
259 schema:givenName Luke
260 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0624766217.74
261 rdf:type schema:Person
262 sg:person.0637727227.25 schema:affiliation grid-institutes:grid.42505.36
263 schema:familyName Sun
264 schema:givenName Fengzhu
265 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0637727227.25
266 rdf:type schema:Person
267 sg:person.0657633746.30 schema:affiliation grid-institutes:grid.42505.36
268 schema:familyName Cram
269 schema:givenName Jacob A
270 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0657633746.30
271 rdf:type schema:Person
272 sg:person.0670257026.89 schema:affiliation grid-institutes:grid.116068.8
273 schema:familyName Friedman
274 schema:givenName Jonathan
275 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0670257026.89
276 rdf:type schema:Person
277 sg:person.0672337357.81 schema:affiliation grid-institutes:grid.241116.1
278 schema:familyName Lozupone
279 schema:givenName Catherine
280 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0672337357.81
281 rdf:type schema:Person
282 sg:person.0725061453.51 schema:affiliation grid-institutes:grid.42505.36
283 schema:familyName Fuhrman
284 schema:givenName Jed A
285 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0725061453.51
286 rdf:type schema:Person
287 sg:person.0765515705.86 schema:affiliation grid-institutes:grid.8767.e
288 schema:familyName Raes
289 schema:givenName Jeroen
290 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0765515705.86
291 rdf:type schema:Person
292 sg:pub.10.1007/978-94-009-4109-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1109716595
293 https://doi.org/10.1007/978-94-009-4109-0
294 rdf:type schema:CreativeWork
295 sg:pub.10.1038/ismej.2010.204 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031320129
296 https://doi.org/10.1038/ismej.2010.204
297 rdf:type schema:CreativeWork
298 sg:pub.10.1038/ismej.2011.24 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007074967
299 https://doi.org/10.1038/ismej.2011.24
300 rdf:type schema:CreativeWork
301 sg:pub.10.1038/ismej.2013.54 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023249054
302 https://doi.org/10.1038/ismej.2013.54
303 rdf:type schema:CreativeWork
304 sg:pub.10.1038/nature07540 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030170002
305 https://doi.org/10.1038/nature07540
306 rdf:type schema:CreativeWork
307 sg:pub.10.1038/nature09922 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043309820
308 https://doi.org/10.1038/nature09922
309 rdf:type schema:CreativeWork
310 sg:pub.10.1038/nature09944 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026204536
311 https://doi.org/10.1038/nature09944
312 rdf:type schema:CreativeWork
313 sg:pub.10.1038/nature13828 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004780748
314 https://doi.org/10.1038/nature13828
315 rdf:type schema:CreativeWork
316 sg:pub.10.1038/nmeth.2658 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002139060
317 https://doi.org/10.1038/nmeth.2658
318 rdf:type schema:CreativeWork
319 sg:pub.10.1038/nrmicro2832 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030236624
320 https://doi.org/10.1038/nrmicro2832
321 rdf:type schema:CreativeWork
322 sg:pub.10.1186/1471-2105-13-113 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032970670
323 https://doi.org/10.1186/1471-2105-13-113
324 rdf:type schema:CreativeWork
325 sg:pub.10.1186/gb-2010-11-10-r106 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031289083
326 https://doi.org/10.1186/gb-2010-11-10-r106
327 rdf:type schema:CreativeWork
328 sg:pub.10.1186/gb-2011-12-5-r50 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050643751
329 https://doi.org/10.1186/gb-2011-12-5-r50
330 rdf:type schema:CreativeWork
331 grid-institutes:None schema:alternateName Biota Technology, Inc., Denver, CO, USA
332 schema:name Biota Technology, Inc., Denver, CO, USA
333 rdf:type schema:Organization
334 grid-institutes:grid.116068.8 schema:alternateName Department of Biological Engineering, Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, MA, USA
335 Department of Physics, Massachusetts Institute of Technology, Cambridge, MA, USA
336 schema:name Department of Biological Engineering, Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, MA, USA
337 Department of Physics, Massachusetts Institute of Technology, Cambridge, MA, USA
338 rdf:type schema:Organization
339 grid-institutes:grid.12527.33 schema:alternateName State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China
340 schema:name Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK, USA
341 Earth Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA
342 State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China
343 rdf:type schema:Organization
344 grid-institutes:grid.241116.1 schema:alternateName Department of Medicine, University of Colorado, Denver, CO, USA
345 schema:name Department of Medicine, University of Colorado, Denver, CO, USA
346 rdf:type schema:Organization
347 grid-institutes:grid.25879.31 schema:alternateName Department of Statistics, The Wharton School, University of Pennsylvania, Philadelphia, PA, USA
348 schema:name Department of Statistics, The Wharton School, University of Pennsylvania, Philadelphia, PA, USA
349 Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
350 rdf:type schema:Organization
351 grid-institutes:grid.266100.3 schema:alternateName Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
352 Department of Medicine, Center for Computational Biology and Bioinformatics, University of California San Diego, La Jolla, CA, USA
353 Departments of Pediatrics, University of California San Diego, La Jolla, CA, USA
354 schema:name Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
355 Department of Medicine, Center for Computational Biology and Bioinformatics, University of California San Diego, La Jolla, CA, USA
356 Departments of Pediatrics, University of California San Diego, La Jolla, CA, USA
357 rdf:type schema:Organization
358 grid-institutes:grid.266190.a schema:alternateName BioFrontiers Institute, University of Colorado at Boulder, Boulder, CO, USA
359 Department of Chemical and Biological Engineering, University of Colorado at Boulder, Boulder, CO, USA
360 schema:name BioFrontiers Institute, University of Colorado at Boulder, Boulder, CO, USA
361 Department of Chemical and Biological Engineering, University of Colorado at Boulder, Boulder, CO, USA
362 rdf:type schema:Organization
363 grid-institutes:grid.266900.b schema:alternateName Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK, USA
364 schema:name CAS Key Laboratory of Environmental Biotechnology, Chinese Academy of Sciences, Beijing, China
365 Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK, USA
366 rdf:type schema:Organization
367 grid-institutes:grid.42505.36 schema:alternateName Department of Biological Sciences, University of Southern California, Los Angeles, CA, USA
368 Molecular and Computational Biology Program, University of Southern California, Los Angeles, California, USA
369 schema:name Department of Biological Sciences, University of Southern California, Los Angeles, CA, USA
370 Molecular and Computational Biology Program, University of Southern California, Los Angeles, California, USA
371 rdf:type schema:Organization
372 grid-institutes:grid.8767.e schema:alternateName Laboratory of Microbiology, Vrije Universiteit Brussel, Brussels, Belgium
373 schema:name Department of Microbiology and Immunology, Rega Institute KU Leuven, Leuven, Belgium
374 Laboratory of Microbiology, Vrije Universiteit Brussel, Brussels, Belgium
375 VIB Center for the Biology of Disease, VIB, Leuven, Belgium
376 rdf:type schema:Organization
 




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


...