2012
DOI: 10.1186/2047-217x-1-7
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The Biological Observation Matrix (BIOM) format or: how I learned to stop worrying and love the ome-ome

Abstract: BackgroundWe present the Biological Observation Matrix (BIOM, pronounced “biome”) format: a JSON-based file format for representing arbitrary observation by sample contingency tables with associated sample and observation metadata. As the number of categories of comparative omics data types (collectively, the “ome-ome”) grows rapidly, a general format to represent and archive this data will facilitate the interoperability of existing bioinformatics tools and future meta-analyses.FindingsThe BIOM file format is… Show more

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Cited by 718 publications
(525 citation statements)
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“…Subsequently, samples were rarefied to contain the same number of reads (n ϭ 5,288), and diversity estimates (the Chao1 richness and Shannon-Weaver diversity indices) were calculated. Taxonomy was assigned to the reads, using the LCAClassifier taxonomic classifier (34), by comparison with the sequences in the Greengenes database (version 13_8) (35), and OTU tables were made with the biological observation matrix (BIOM) format (36) and imported into SigmaPlot software (version 12.0; Systat Software, Inc., CA, USA) to make plots and perform statistical analyses on relative OTU abundances. Where possible, OTUs were assigned to the genus level; however, some OTUs could not be determined to a level lower than class, order, or family.…”
Section: Methodsmentioning
confidence: 99%
“…Subsequently, samples were rarefied to contain the same number of reads (n ϭ 5,288), and diversity estimates (the Chao1 richness and Shannon-Weaver diversity indices) were calculated. Taxonomy was assigned to the reads, using the LCAClassifier taxonomic classifier (34), by comparison with the sequences in the Greengenes database (version 13_8) (35), and OTU tables were made with the biological observation matrix (BIOM) format (36) and imported into SigmaPlot software (version 12.0; Systat Software, Inc., CA, USA) to make plots and perform statistical analyses on relative OTU abundances. Where possible, OTUs were assigned to the genus level; however, some OTUs could not be determined to a level lower than class, order, or family.…”
Section: Methodsmentioning
confidence: 99%
“…All chimera-checked and quality-filtered sequences were clustered into operational taxonomic units (OTUs) at a 97% identity cutoff, and clusters were assigned taxonomic designations using the greengenes database (13_8 97). After clustering and .biom table (93) creation, all singleton, chloroplast, insect, mitochondrial, and unclassified clusters were removed from the data set; these clusters represented sequences that were ϳ0.2% of the total number of sequences in the data set.…”
Section: Methodsmentioning
confidence: 99%
“…Quality control processing and singleton removal was carried out via the UPARSE pipeline (for example, usearch -fastq_ maxee 0.5, usearch -sortbysize -minsize 2) including de novo and reference-based chimera detection (Edgar, 2013). The resulting operational taxonomic unit (OTU) table was converted to Biological Observation Matrix (BIOM) format (McDonald et al, 2012a). Taxonomy was assigned using the Ribosomal Database Project (RDP) classifier (Wang et al, 2007) against the updated May 2013 '13_5/13_8' Greengenes database (Werner et al, 2011;McDonald et al, 2012b) via the parallel_assign_taxonomy_rdp.py script in QIIME.…”
Section: Amplicon Sequencing and Analysismentioning
confidence: 99%