ADDAGMA: A database for domestic animal gut microbiome atlas
ADDAGMA: A database for domestic animal gut microbiome atlas is a dataset published in Computational and Structural Biotechnology Journal (2022). On theSindex it has a DataRank of 0.693, placing it in the top 45.3% of the data-sharing corpus. It has been cited 19 times, with 19 citing works in its 1-hop citation network. Its calibrated FAIR score is 53/100.
Abstract
Animal gut microbiomes play important roles in the health, diseases, and production of animal hosts. The volume of animal gut metagenomic data, including both 16S amplicon and metagenomic sequencing data, has been increasing exponentially in recent years, making it increasingly difficult for researchers to query, retrieve, and reanalyze experimental data and explore new hypotheses. We designed a database called the domestic animal gut microbiome atlas (ADDAGMA) to house all publicly available, high-throughput sequencing data for the gut microbiome in domestic animals. ADDAGMA enhances the availability and accessibility of the rapidly growing body of metagenomic data. We annotated microbial and metadata from four domestic animals (cattle, horse, pig, and chicken) from 356 published papers to construct a comprehensive database that is equipped with browse and search functions, enabling users to make customized, complicated, biologically relevant queries. Users can quickly and accurately obtain experimental information on sample types, conditions, and sequencing platforms, and experimental results including microbial relative abundances, microbial taxon-associated host phenotype, and P-values for gut microbes of interest. The current version of ADDAGMA includes 290,422 quantification events (changes in abundance) for 3215 microbial taxa associated with 48 phenotypes. ADDAGMA presently covers gut microbiota sequencing data from pig, cattle, horse, and chicken, but will be expanded to include other domestic animals. ADDAGMA is freely available at (http://addagma.omicsbio.info/).
›Data sources & pipeline
FAIR Checklist
Context only (not used in score)- Has DOI
- Open Access
- Dataset classification
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Calibrated FAIR score — a parallel quality metric, independent of the DataRank citation score. See the full evaluation →
DataRank Breakdown
Base Score Contribution
0.442
From this paper's citation signal
Citation Network Contribution
0.252
From 13 citing papers with measurable signal
Top 5 citers driving the network score
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
- Search and clustering orders of magnitude faster than BLASTBioinformatics201021,556 citationsDataRank 1.5
- VSEARCH: a versatile open source tool for metagenomicsPeerJ201610,782 citationsDataRank 1.4
- The sequence read archive: explosive growth of sequencing dataNucleic Acids Research2011970 citationsDataRank 20.1Top 5%
- GMrepo: a database of curated and consistently annotated human gut metagenomesNucleic Acids Research2019183 citationsDataRank 5.4Top 28%
- The European Nucleotide Archive in 2018Nucleic Acids Research2018127 citationsDataRank 5.3Top 28%
Why this DataRank?
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 64% comes from its base citations and 36% from the citation network (13 citing papers contributed measurable signal).
- Base score B(p)
- log1p(citation_count) — grows sub-linearly, so a paper with 1,000 citations is not 10× a paper with 100.
- Network N(p)
- Σ over citers of log1p(Cq) ÷ max(outdegreeq, 1). Being cited by a highly-cited paper with few references counts most.
- Damping factor d = 0.85
- DataRank = (1−d)·B(p) + d·N(p) — the two cards above are each already multiplied by their share.
- Self-citations excluded
- Citers sharing any OpenAlex author ID with this paper are filtered out before the network sum.
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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