BugSigDB captures patterns of differential abundance across a broad range of host-associated microbial signatures
The literature of human and other host-associated microbiome studies is expanding rapidly, but systematic comparisons among published results of host-associated microbiome signatures of differential abundance remain difficult. We present BugSigDB, a community-editable database of manually curated mi...
| Main Authors: | , , , , , , , , , , , , , , , , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Nature Research
2023
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| _version_ | 1811140087244652544 |
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| author | Geistlinger, L Mirzayi, C Zohra, F Azhar, R Elsafoury, S Grieve, C Wokaty, J Gamboa-Tuz, SD Sengupta, P Hecht, I Ravikrishnan, A Gonçalves, RS Franzosa, E Raman, K Carey, V Dowd, JB Jones, HE Davis, S Segata, N Huttenhower, C Waldron, L |
| author_facet | Geistlinger, L Mirzayi, C Zohra, F Azhar, R Elsafoury, S Grieve, C Wokaty, J Gamboa-Tuz, SD Sengupta, P Hecht, I Ravikrishnan, A Gonçalves, RS Franzosa, E Raman, K Carey, V Dowd, JB Jones, HE Davis, S Segata, N Huttenhower, C Waldron, L |
| author_sort | Geistlinger, L |
| collection | OXFORD |
| description | The literature of human and other host-associated microbiome studies is expanding rapidly, but systematic comparisons among published results of host-associated microbiome signatures of differential abundance remain difficult. We present BugSigDB, a community-editable database of manually curated microbial signatures from published differential abundance studies accompanied by information on study geography, health outcomes, host body site and experimental, epidemiological and statistical methods using controlled vocabulary. The initial release of the database contains >2,500 manually curated signatures from >600 published studies on three host species, enabling high-throughput analysis of signature similarity, taxon enrichment, co-occurrence and coexclusion and consensus signatures. These data allow assessment of microbiome differential abundance within and across experimental conditions, environments or body sites. Database-wide analysis reveals experimental conditions with the highest level of consistency in signatures reported by independent studies and identifies commonalities among disease-associated signatures, including frequent introgression of oral pathobionts into the gut. |
| first_indexed | 2024-09-25T04:16:24Z |
| format | Journal article |
| id | oxford-uuid:018f122b-db15-47e0-b0eb-eb03e5ef69f3 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-09-25T04:16:24Z |
| publishDate | 2023 |
| publisher | Nature Research |
| record_format | dspace |
| spelling | oxford-uuid:018f122b-db15-47e0-b0eb-eb03e5ef69f32024-07-20T15:45:29ZBugSigDB captures patterns of differential abundance across a broad range of host-associated microbial signaturesJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:018f122b-db15-47e0-b0eb-eb03e5ef69f3EnglishJisc Publications RouterNature Research2023Geistlinger, LMirzayi, CZohra, FAzhar, RElsafoury, SGrieve, CWokaty, JGamboa-Tuz, SDSengupta, PHecht, IRavikrishnan, AGonçalves, RSFranzosa, ERaman, KCarey, VDowd, JBJones, HEDavis, SSegata, NHuttenhower, CWaldron, LThe literature of human and other host-associated microbiome studies is expanding rapidly, but systematic comparisons among published results of host-associated microbiome signatures of differential abundance remain difficult. We present BugSigDB, a community-editable database of manually curated microbial signatures from published differential abundance studies accompanied by information on study geography, health outcomes, host body site and experimental, epidemiological and statistical methods using controlled vocabulary. The initial release of the database contains >2,500 manually curated signatures from >600 published studies on three host species, enabling high-throughput analysis of signature similarity, taxon enrichment, co-occurrence and coexclusion and consensus signatures. These data allow assessment of microbiome differential abundance within and across experimental conditions, environments or body sites. Database-wide analysis reveals experimental conditions with the highest level of consistency in signatures reported by independent studies and identifies commonalities among disease-associated signatures, including frequent introgression of oral pathobionts into the gut. |
| spellingShingle | Geistlinger, L Mirzayi, C Zohra, F Azhar, R Elsafoury, S Grieve, C Wokaty, J Gamboa-Tuz, SD Sengupta, P Hecht, I Ravikrishnan, A Gonçalves, RS Franzosa, E Raman, K Carey, V Dowd, JB Jones, HE Davis, S Segata, N Huttenhower, C Waldron, L BugSigDB captures patterns of differential abundance across a broad range of host-associated microbial signatures |
| title | BugSigDB captures patterns of differential abundance across a broad range of host-associated microbial signatures |
| title_full | BugSigDB captures patterns of differential abundance across a broad range of host-associated microbial signatures |
| title_fullStr | BugSigDB captures patterns of differential abundance across a broad range of host-associated microbial signatures |
| title_full_unstemmed | BugSigDB captures patterns of differential abundance across a broad range of host-associated microbial signatures |
| title_short | BugSigDB captures patterns of differential abundance across a broad range of host-associated microbial signatures |
| title_sort | bugsigdb captures patterns of differential abundance across a broad range of host associated microbial signatures |
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