Microbial Co-occurrence Relationships in the Human Microbiome
Publication Date
July 12, 2012
Journal
PLOS Computational Biology
Authors
Karoline Faust, J. Fah Sathirapongsasuti, Jacques Izard, Nicola Segata, et al
Volume
8
Issue
7
Pages
e1002606
DOI
https://dx.plos.org/10.1371/journal.pcbi.1002606
Publisher URL
http://journals.plos.org/ploscompbiol/article?id=10.1371%2Fjournal.pcbi.1002606
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/22807668
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3395616
Europe PMC
http://europepmc.org/abstract/MED/22807668
Web of Science
000306842200029
Scopus
84864579031
Mendeley
http://www.mendeley.com/research/microbial-cooccurrence-relationships-human-microbiome
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{"title"=>"Microbial co-occurrence relationships in the Human Microbiome", "type"=>"journal", "authors"=>[{"first_name"=>"Karoline", "last_name"=>"Faust", "scopus_author_id"=>"24484851700"}, {"first_name"=>"J. Fah", "last_name"=>"Sathirapongsasuti", "scopus_author_id"=>"37073152400"}, {"first_name"=>"Jacques", "last_name"=>"Izard", "scopus_author_id"=>"36808779100"}, {"first_name"=>"Nicola", "last_name"=>"Segata", "scopus_author_id"=>"14016713700"}, {"first_name"=>"Dirk", "last_name"=>"Gevers", "scopus_author_id"=>"6603379365"}, {"first_name"=>"Jeroen", "last_name"=>"Raes", "scopus_author_id"=>"8602126700"}, {"first_name"=>"Curtis", "last_name"=>"Huttenhower", "scopus_author_id"=>"14521138100"}], "year"=>2012, "source"=>"PLoS Computational Biology", "identifiers"=>{"scopus"=>"2-s2.0-84864579031", "doi"=>"10.1371/journal.pcbi.1002606", "sgr"=>"84864579031", "isbn"=>"10.1371/journal.pcbi.1002606", "pmid"=>"22807668", "issn"=>"1553734X", "pui"=>"365384813"}, "id"=>"fb9167f8-f9ac-327e-b9c7-24fbc1a042ae", "abstract"=>"The healthy microbiota show remarkable variability within and among individuals. In addition to external exposures, ecological relationships (both oppositional and symbiotic) between microbial inhabitants are important contributors to this variation. It is thus of interest to assess what relationships might exist among microbes and determine their underlying reasons. The initial Human Microbiome Project (HMP) cohort, comprising 239 individuals and 18 different microbial habitats, provides an unprecedented resource to detect, catalog, and analyze such relationships. Here, we applied an ensemble method based on multiple similarity measures in combination with generalized boosted linear models (GBLMs) to taxonomic marker (16S rRNA gene) profiles of this cohort, resulting in a global network of 3,005 significant co-occurrence and co-exclusion relationships between 197 clades occurring throughout the human microbiome. This network revealed strong niche specialization, with most microbial associations occurring within body sites and a number of accompanying inter-body site relationships. Microbial communities within the oropharynx grouped into three distinct habitats, which themselves showed no direct influence on the composition of the gut microbiota. Conversely, niches such as the vagina demonstrated little to no decomposition into region-specific interactions. Diverse mechanisms underlay individual interactions, with some such as the co-exclusion of Porphyromonaceae family members and Streptococcus in the subgingival plaque supported by known biochemical dependencies. These differences varied among broad phylogenetic groups as well, with the Bacilli and Fusobacteria, for example, both enriched for exclusion of taxa from other clades. Comparing phylogenetic versus functional similarities among bacteria, we show that dominant commensal taxa (such as Prevotellaceae and Bacteroides in the gut) often compete, while potential pathogens (e.g. Treponema and Prevotella in the dental plaque) are more likely to co-occur in complementary niches. This approach thus serves to open new opportunities for future targeted mechanistic studies of the microbial ecology of the human microbiome.", "link"=>"http://www.mendeley.com/research/microbial-cooccurrence-relationships-human-microbiome", "reader_count"=>955, "reader_count_by_academic_status"=>{"Unspecified"=>20, "Professor > Associate Professor"=>44, "Researcher"=>234, "Student > Doctoral Student"=>48, "Student > Ph. D. Student"=>305, "Student > Postgraduate"=>31, "Student > Master"=>131, "Other"=>26, "Student > Bachelor"=>74, "Lecturer"=>9, "Lecturer > Senior Lecturer"=>4, "Professor"=>29}, "reader_count_by_user_role"=>{"Unspecified"=>20, "Professor > Associate Professor"=>44, "Researcher"=>234, "Student > Doctoral Student"=>48, "Student > Ph. D. Student"=>305, "Student > Postgraduate"=>31, "Student > Master"=>131, "Other"=>26, "Student > Bachelor"=>74, "Lecturer"=>9, "Lecturer > Senior Lecturer"=>4, "Professor"=>29}, "reader_count_by_subject_area"=>{"Unspecified"=>41, "Agricultural and Biological Sciences"=>559, "Arts and Humanities"=>4, "Philosophy"=>1, "Business, Management and Accounting"=>1, "Veterinary Science and Veterinary Medicine"=>3, "Chemical Engineering"=>1, "Chemistry"=>9, "Computer Science"=>33, "Earth and Planetary Sciences"=>5, "Engineering"=>16, "Environmental Science"=>54, "Biochemistry, Genetics and Molecular Biology"=>92, "Nursing and Health Professions"=>1, "Materials Science"=>1, "Mathematics"=>15, "Medicine and Dentistry"=>54, "Pharmacology, Toxicology and Pharmaceutical Science"=>2, "Physics and Astronomy"=>17, "Social Sciences"=>4, "Immunology and Microbiology"=>42}, "reader_count_by_subdiscipline"=>{"Materials Science"=>{"Materials Science"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>54}, "Social Sciences"=>{"Social Sciences"=>4}, "Physics and Astronomy"=>{"Physics and Astronomy"=>17}, "Mathematics"=>{"Mathematics"=>15}, "Unspecified"=>{"Unspecified"=>41}, "Environmental Science"=>{"Environmental Science"=>54}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>2}, "Chemical Engineering"=>{"Chemical Engineering"=>1}, "Arts and Humanities"=>{"Arts and Humanities"=>4}, "Engineering"=>{"Engineering"=>16}, "Chemistry"=>{"Chemistry"=>9}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>5}, "Immunology and Microbiology"=>{"Immunology and Microbiology"=>42}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>559}, "Computer Science"=>{"Computer Science"=>33}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>1}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>92}, "Philosophy"=>{"Philosophy"=>1}, "Veterinary Science and Veterinary Medicine"=>{"Veterinary Science and Veterinary Medicine"=>3}}, "reader_count_by_country"=>{"Hong Kong"=>1, "United States"=>57, "Portugal"=>3, "Russia"=>2, "Sweden"=>2, "Netherlands"=>3, "Austria"=>2, "Iran"=>1, "Ireland"=>1, "Brazil"=>5, "France"=>11, "Nigeria"=>1, "Chile"=>1, "Japan"=>2, "United Kingdom"=>6, "Switzerland"=>1, "Spain"=>4, "India"=>3, "New Zealand"=>1, "Canada"=>7, "Belgium"=>4, "Finland"=>1, "Denmark"=>8, "Mexico"=>2, "South Africa"=>2, "Italy"=>1, "Australia"=>1, "Germany"=>6, "Estonia"=>2}, "group_count"=>52}

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  • {"files"=>["https://ndownloader.figshare.com/files/318800", "https://ndownloader.figshare.com/files/318850", "https://ndownloader.figshare.com/files/318909", "https://ndownloader.figshare.com/files/318954", "https://ndownloader.figshare.com/files/318982", "https://ndownloader.figshare.com/files/319011", "https://ndownloader.figshare.com/files/319054", "https://ndownloader.figshare.com/files/319101", "https://ndownloader.figshare.com/files/319164", "https://ndownloader.figshare.com/files/319256", "https://ndownloader.figshare.com/files/319331", "https://ndownloader.figshare.com/files/319344", "https://ndownloader.figshare.com/files/319380"], "description"=>"<div><p>The healthy microbiota show remarkable variability within and among individuals. In addition to external exposures, ecological relationships (both oppositional and symbiotic) between microbial inhabitants are important contributors to this variation. It is thus of interest to assess what relationships might exist among microbes and determine their underlying reasons. The initial Human Microbiome Project (HMP) cohort, comprising 239 individuals and 18 different microbial habitats, provides an unprecedented resource to detect, catalog, and analyze such relationships. Here, we applied an ensemble method based on multiple similarity measures in combination with generalized boosted linear models (GBLMs) to taxonomic marker (16S rRNA gene) profiles of this cohort, resulting in a global network of 3,005 significant co-occurrence and co-exclusion relationships between 197 clades occurring throughout the human microbiome. This network revealed strong niche specialization, with most microbial associations occurring within body sites and a number of accompanying inter-body site relationships. Microbial communities within the oropharynx grouped into three distinct habitats, which themselves showed no direct influence on the composition of the gut microbiota. Conversely, niches such as the vagina demonstrated little to no decomposition into region-specific interactions. Diverse mechanisms underlay individual interactions, with some such as the co-exclusion of Porphyromonaceae family members and <em>Streptococcus</em> in the subgingival plaque supported by known biochemical dependencies. These differences varied among broad phylogenetic groups as well, with the Bacilli and Fusobacteria, for example, both enriched for exclusion of taxa from other clades. Comparing phylogenetic versus functional similarities among bacteria, we show that dominant commensal taxa (such as Prevotellaceae and <em>Bacteroides</em> in the gut) often compete, while potential pathogens (e.g. <em>Treponema</em> and <em>Prevotella</em> in the dental plaque) are more likely to co-occur in complementary niches. This approach thus serves to open new opportunities for future targeted mechanistic studies of the microbial ecology of the human microbiome.</p> </div>", "links"=>[], "tags"=>["microbial", "co-occurrence", "relationships", "microbiome"], "article_id"=>122921, "categories"=>["Mathematics", "Biological Sciences", "Microbiology"], "users"=>["Karoline Faust", "J. Fah Sathirapongsasuti", "Jacques Izard", "Nicola Segata", "Dirk Gevers", "Jeroen Raes", "Curtis Huttenhower"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1002606.s001", "https://dx.doi.org/10.1371/journal.pcbi.1002606.s002", "https://dx.doi.org/10.1371/journal.pcbi.1002606.s003", "https://dx.doi.org/10.1371/journal.pcbi.1002606.s004", "https://dx.doi.org/10.1371/journal.pcbi.1002606.s005", "https://dx.doi.org/10.1371/journal.pcbi.1002606.s006", "https://dx.doi.org/10.1371/journal.pcbi.1002606.s007", "https://dx.doi.org/10.1371/journal.pcbi.1002606.s008", "https://dx.doi.org/10.1371/journal.pcbi.1002606.s009", "https://dx.doi.org/10.1371/journal.pcbi.1002606.s010", "https://dx.doi.org/10.1371/journal.pcbi.1002606.s011", "https://dx.doi.org/10.1371/journal.pcbi.1002606.s012", "https://dx.doi.org/10.1371/journal.pcbi.1002606.s013"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Microbial_Co_occurrence_Relationships_in_the_Human_Microbiome/122921", "title"=>"Microbial Co-occurrence Relationships in the Human Microbiome", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2012-07-12 00:48:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/610080"], "description"=>"<p>16S data from the Human Microbiome Project (HMP) were collected from 18 body sites in a cohort of 239 healthy subjects and assessed using 16S rRNA gene sequencing. We analyzed microbial co-occurrence and co-exclusion patterns in these data by developing two complementary approaches: a compendium of Generalized Boosted Linear Model (GBLMs) and an ensemble of similarity and dissimilarity measures. Each approach produced a network in which each node represented a microbial taxon within one body site, and each edge represented a significant association between microbial or whole clade abundances within or across body sites. The resulting association networks produced by each individual method were merged as p-values using Simes method, after which FDR correction was performed. Associations with FDR q-values>0.05, inconclusive directionality, or fewer than two supporting pieces of evidence were removed. This provided a single global microbial association network for taxa throughout the healthy commensal microbiota.</p>", "links"=>[], "tags"=>["characterizing", "microbial", "interactions", "compendium"], "article_id"=>280554, "categories"=>["Mathematics", "Biological Sciences", "Microbiology"], "users"=>["Karoline Faust", "J. Fah Sathirapongsasuti", "Jacques Izard", "Nicola Segata", "Dirk Gevers", "Jeroen Raes", "Curtis Huttenhower"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1002606.g001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Methodology_for_characterizing_microbial_interactions_using_a_compendium_of_similarity_measures_/280554", "title"=>"Methodology for characterizing microbial interactions using a compendium of similarity measures.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-07-12 00:09:14"}
  • {"files"=>["https://ndownloader.figshare.com/files/610204"], "description"=>"<p>A global microbial interaction network capturing 1,949 associations among 452 clades at or above the order level in the human microbiome, reduced for visualization from the complete network in <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002606#pcbi.1002606.s001\" target=\"_blank\">Figure S1</a>. Each node represents a bacterial order, summarizing one or more genus-level phylotypes and family-level taxonomic groups. These are colored by body site, and each edge represents a significant co-occurrence/co-exclusion relationship. Edge width is proportional to the significance of supporting evidence, and color indicates the sign of the association (red negative, green positive). Self-loops indicate associations among phylotypes within an order; for a full network of all phylotypes and clades, see <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002606#pcbi.1002606.s001\" target=\"_blank\">Figure S1</a>. A high degree of modularity is apparent within body areas (skin, urogenital tract, oral cavity, gut, and airways) and within individual body sites, with most communities forming distinct niches across which few microbial associations occur.</p>", "links"=>[], "tags"=>["co-occurrence", "co-exclusion", "relationships", "abundances", "clades"], "article_id"=>280678, "categories"=>["Mathematics", "Biological Sciences", "Microbiology"], "users"=>["Karoline Faust", "J. Fah Sathirapongsasuti", "Jacques Izard", "Nicola Segata", "Dirk Gevers", "Jeroen Raes", "Curtis Huttenhower"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1002606.g002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Significant_co_occurrence_and_co_exclusion_relationships_among_the_abundances_of_clades_in_the_human_microbiome_/280678", "title"=>"Significant co-occurrence and co-exclusion relationships among the abundances of clades in the human microbiome.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-07-12 00:11:18"}
  • {"files"=>["https://ndownloader.figshare.com/files/610364"], "description"=>"<p>A) Node degree distributions of overall, co-occurrence, and co-exclusion associations in the human microbiome. This is well-fit by a power law with slope −1,7 (dotted red regression line, adjusted R<sup>2</sup> = 0.9). Node degree indicates the number of links that connect a node to others in the network. Power law degree distributions, referred to as scale-free, mean that most nodes have only a few edges and are often connected by a few high-degree hub nodes. The top five most connected hubs as indicated in callouts, mainly signature oral taxa including <i>Porphyromonas</i> in the tongue dorsum. B) and C) Node proportions after division of the network into body sites (B) or classes (C). Both pie charts show that the composition of the network (in agreement with underlying data) is skewed towards the oral cavity (B) and its constituent Firmicutes (including Bacilli and Clostridia) (C). (B) further agrees with published measures of body sites' alpha diversity <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002606#pcbi.1002606-Costello1\" target=\"_blank\">[84]</a>. D) and E) Composition of relationships among microbes grouped according to body site (D) and taxonomic class (E). In E), the first two bars (green and red) include the fraction of all possible edges incident to at least one node representing a class or one of its members (root scaled for visualization). The second two bars (lime and orange) only include pairs of microbes that are members of the same class, again normalized as a fraction of total possible interactions and root scaled. The Bacilli, Bacteroidia, and Fusobacteria contain significantly more negatively associated microbes than expected by permutation testing (see <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002606#pcbi.1002606.s011\" target=\"_blank\">Table S2</a>), and classes overall are depleted for negative associations, indicating that members of the same class tend not to compete strongly with each other in these communities.</p>", "links"=>[], "tags"=>["properties", "summarizing", "microbial", "hubs"], "article_id"=>280838, "categories"=>["Mathematics", "Biological Sciences", "Microbiology"], "users"=>["Karoline Faust", "J. Fah Sathirapongsasuti", "Jacques Izard", "Nicola Segata", "Dirk Gevers", "Jeroen Raes", "Curtis Huttenhower"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1002606.g003"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Global_network_properties_summarizing_key_microbial_hubs_and_interaction_patterns_/280838", "title"=>"Global network properties summarizing key microbial hubs and interaction patterns.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-07-12 00:13:58"}
  • {"files"=>["https://ndownloader.figshare.com/files/610502"], "description"=>"<p>Nodes represent microbial classes colored by phylum, with edges summarizing aspects of their interactions over all body sites. Classes are linked when the number of edges between them is significantly larger than expected (randomization p<0.05, see <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002606#s3\" target=\"_blank\">Methods</a>). Edge type (solid or dashed) indicates the body area contributing the most edges to the total interactions between two classes, with the label specifying the percentage contributed by this dominant body area. For instance, 80% of the edges between Bacilli and Actinobacteria come from skin sites. Green indicates co-occurrence, red exclusion. Most inter-class interactions occur in the mouth, with the Actinobacteria and Bacilli forming negative hubs.</p>", "links"=>[], "tags"=>["microbial", "clades"], "article_id"=>280987, "categories"=>["Mathematics", "Biological Sciences", "Microbiology"], "users"=>["Karoline Faust", "J. Fah Sathirapongsasuti", "Jacques Izard", "Nicola Segata", "Dirk Gevers", "Jeroen Raes", "Curtis Huttenhower"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1002606.g004"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Co_occurrence_of_microbial_clades_within_and_among_body_areas_/280987", "title"=>"Co-occurrence of microbial clades within and among body areas.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-07-12 00:16:27"}
  • {"files"=>["https://ndownloader.figshare.com/files/610625"], "description"=>"<p>Each node represents a body site, with edge width indicating significant cross-site correlations (randomization p<0.05, see <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002606#s3\" target=\"_blank\">Methods</a>). Green edges show co-occurrence, red co-exclusion. Skin, vaginal, oral soft tissue, and tooth plaque moieties are apparent, with the gut and airways notably lacking significant interactions with other available body site niches. However, most relationships between microbial relative abundances occur specifically within, rather than between, individual body sites.</p>", "links"=>[], "tags"=>["microbial", "niches", "associations", "spanning", "habitats"], "article_id"=>281101, "categories"=>["Mathematics", "Biological Sciences", "Microbiology"], "users"=>["Karoline Faust", "J. Fah Sathirapongsasuti", "Jacques Izard", "Nicola Segata", "Dirk Gevers", "Jeroen Raes", "Curtis Huttenhower"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1002606.g005"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Related_microbial_niches_as_determined_by_associations_spanning_habitats_at_multiple_human_body_sites_/281101", "title"=>"Related microbial niches as determined by associations spanning habitats at multiple human body sites.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-07-12 00:18:21"}
  • {"files"=>["https://ndownloader.figshare.com/files/610719"], "description"=>"<p>Evolutionary (phylogenetic) distances among microbial clades were compared to the clades' functional potentials as defined by the Jaccard index of orthologous gene (COG) families shared between genomes (see <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002606#s3\" target=\"_blank\">Methods</a>). Each point represents a pair of significantly associated microbes colored by direction of the association (green positive, red negative) and shaped by the type of relationship (triangle: between body sites, square: within site). Phylogenetic distances were inferred by FastTree <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002606#pcbi.1002606-Price1\" target=\"_blank\">[82]</a> using species-level 16S sequences. Most interactions lie along the diagonal, reflecting the baseline correlation between these functional and evolutionary distances, with highly related clades co-occurring among related habitats (e.g. bilateral skin sites, proximal oral sites) in the lower left. Off-diagonal examples include potential competition among dominant gut signature taxa (e.g. Prevotellaceae/<i>Bacteroides</i>) and functional complementarity between distinct oral pathogens (e.g. <i>Treponema</i>/<i>Prevotella</i>).</p>", "links"=>[], "tags"=>["phylogenetic", "similarities", "co-occurring"], "article_id"=>281197, "categories"=>["Mathematics", "Biological Sciences", "Microbiology"], "users"=>["Karoline Faust", "J. Fah Sathirapongsasuti", "Jacques Izard", "Nicola Segata", "Dirk Gevers", "Jeroen Raes", "Curtis Huttenhower"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1002606.g006"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Functional_and_phylogenetic_similarities_between_co_occurring_microbes_/281197", "title"=>"Functional and phylogenetic similarities between co-occurring microbes.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-07-12 00:19:57"}
  • {"files"=>["https://ndownloader.figshare.com/files/610822"], "description"=>"<p>We considered microbial associations in a total of 5,026 samples from the Human Microbiome Project (HMP) comprising 18 body sites in 239 individuals recruited at two clinical centers (Baylor College of Medicine, Houston, TX and Washington University at St. Louis, MO), which in total contained 726 reliably detectable bacterial phylotypes. For details of HMP samples and data processing, see <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002606#pcbi.1002606-The1\" target=\"_blank\">[29]</a>.</p>", "links"=>[], "tags"=>["rrna", "sequencing", "microbiome", "microbial", "co-occurrence", "relationships"], "article_id"=>281295, "categories"=>["Mathematics", "Biological Sciences", "Microbiology"], "users"=>["Karoline Faust", "J. Fah Sathirapongsasuti", "Jacques Izard", "Nicola Segata", "Dirk Gevers", "Jeroen Raes", "Curtis Huttenhower"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1002606.t001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_16S_rRNA_gene_sequencing_data_from_the_Human_Microbiome_Project_used_to_assess_microbial_co_occurrence_relationships_in_the_human_microbiome_/281295", "title"=>"16S rRNA gene sequencing data from the Human Microbiome Project used to assess microbial co-occurrence relationships in the human microbiome.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-07-12 00:21:35"}
  • {"files"=>["https://ndownloader.figshare.com/files/610865"], "description"=>"<p>Microbial co-occurrence and co-exclusion relationships summarized within the five major body areas and relationships spanning different body sites within these areas. Percentages are fractions of the total number of edges in the network, while percentages in parentheses represent fractions of edges within each body area.</p>", "links"=>[], "tags"=>["microbial", "associations"], "article_id"=>281348, "categories"=>["Mathematics", "Biological Sciences", "Microbiology"], "users"=>["Karoline Faust", "J. Fah Sathirapongsasuti", "Jacques Izard", "Nicola Segata", "Dirk Gevers", "Jeroen Raes", "Curtis Huttenhower"], "doi"=>["https://dx.doi.org/10.1371/journal.pcbi.1002606.t002"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Summary_statistics_of_microbial_associations_in_the_normal_human_microbiota_/281348", "title"=>"Summary statistics of microbial associations in the normal human microbiota.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-07-12 00:22:28"}

PMC Usage Stats | Further Information

  • {"unique-ip"=>"99", "full-text"=>"129", "pdf"=>"59", "abstract"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"62", "supp-data"=>"4", "cited-by"=>"0", "year"=>"2012", "month"=>"7"}
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