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GigaScience  2012 

The Biological Observation Matrix (BIOM) format or: how I learned to stop worrying and love the ome-ome

DOI: 10.1186/2047-217x-1-7

Keywords: Microbial ecology, Comparative genomics, Metagenomics, QIIME, MG-RAST, VAMPS, BIOM

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Abstract:

The BIOM file format is supported by an independent open-source software project (the biom-format project), which initially contains Python objects that support the use and manipulation of BIOM data in Python programs, and is intended to be an open development effort where developers can submit implementations of these objects in other programming languages.The BIOM file format and the biom-format project are steps toward reducing the “bioinformatics bottleneck” that is currently being experienced in diverse areas of biological sciences, and will help us move toward the next phase of comparative omics where basic science is translated into clinical and environmental applications. The BIOM file format is currently recognized as an Earth Microbiome Project Standard, and as a Candidate Standard by the Genomic Standards Consortium.Advances in DNA sequencing have led to exponential increases in the quantity of data available for “comparative omics” analyses, including metagenomics (e.g., [1,2]), comparative genomics (e.g., [3]), metatranscriptomics (e.g., [4,5]), and marker-gene-based community surveys (e.g., [6,7]). With the introduction of a new generation of "benchtop sequencers" [8], accessible to small research, clinical, and educational laboratories, sequence-based comparative omic studies will continue to increase in scale. The rate-limiting step in many areas of comparative omics is no longer obtaining data, but analyzing that data (the “bioinformatics bottleneck”) [9,10]. One mechanism that will help reduce this “bioinformatics bottleneck” is standardization of common file formats to facilitate sharing and archiving of data [11].As with the increasing prevalence of high-throughput technologies in the biological sciences, the categories of comparative omics data, which we collectively term the “ome-ome”, are rapidly increasing in number (Figure 1). Researchers are relying on more types of omics data to investigate biological systems, and the coming years will bri

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