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KAUST Metagenomic Analysis Platform (KMAP), Enabling Access to Massive Analytics of Re-Annotated Metagenomic Data.
KAUST DepartmentComputational Bioscience Research Center (CBRC)
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Biological and Environmental Sciences and Engineering (BESE) Division
Marine Science Program
Red Sea Research Center (RSRC)
Applied Mathematics and Computational Science Program
Permanent link to this recordhttp://hdl.handle.net/10754/666521.1
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AbstractAbstract Exponential rise of metagenomics sequencing is delivering massive functional environmental genomics data. However, this also generates a procedural bottleneck for on-going re-analysis as reference databases grow and methods improve, and analyses need be updated for consistency, which require acceess to increasingly demanding bioinformatic and computational resources. Here, we present the KAUST Metagenomic Analysis Platform (KMAP), a new integrated open web-based tool for the comprehensive exploration of shotgun metagenomic data. We illustrate the capacities KMAP provides through the re-assembly of ~27,000 public metagenomic samples captured in ~450 studies sampled across ~77 diverse habitats, resulting in 36 new habitat-specific gene catalogs, all based on full-length (complete) genes. Extensive taxonomic and gene annotations are stored in Gene Information Tables (GITs), a simple tractable data integration format useful for analysis through command line or for database management. KMAP facilitates the exploration and comparison of microbial GITs across different habitats with over 275 million genes.
CitationAlam, I., Kamau, A., Gugi, D., Gojobori, T., Duarte, C., & Bajic, V. (2020). KAUST Metagenomic Analysis Platform (KMAP), Enabling Access to Massive Analytics of Re-Annotated Metagenomic Data. doi:10.21203/rs.3.rs-119704/v1
PublisherResearch Square Platform LLC
CollectionsBiological and Environmental Science and Engineering (BESE) Division; Red Sea Research Center (RSRC); Preprints; Bioscience Program; Marine Science Program; Applied Mathematics and Computational Science Program; Computational Bioscience Research Center (CBRC); Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
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