KAUST Metagenomic Analysis Platform (KMAP), enabling access to massive analytics of re-annotated metagenomic data

Abstract 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 requir...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Intikhab Alam, Allan Anthony Kamau, David Kamanda Ngugi, Takashi Gojobori, Carlos M. Duarte, Vladimir B. Bajic
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
Materias:
R
Q
Acceso en línea:https://doaj.org/article/862b99f21ed745569d475bc35f802129
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
Descripción
Sumario:Abstract 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. A small subset of these metagenomic assemblies is used in this pilot study grouped into 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 pilot study provides the exploration and comparison of microbial GITs across different habitats with over 275 million genes. KMAP access to data and analyses is available at https://www.cbrc.kaust.edu.sa/aamg/kmap.start .