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Research Article
Intikhab Alam
King Abdullah University of Science and Technology
Corresponding Author
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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.
Keywords
Shotgun Metagenomics, Gene Catalogs, Gene Information Tables, Comparative Metagenomics, Industrial Genes, Artificial Intelligence
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CURRENT STATUS: Under Review
Version 1
Posted 14 Dec, 2020
No community comments so far
Editorial decision: Major revision
On 02 Feb, 2021
Reviews received
Received 26 Jan, 2021
Reviewers agreed
On 24 Jan, 2021
Reviews received
Received 22 Jan, 2021
Reviewers agreed
On 14 Dec, 2020
Reviewers agreed
On 11 Dec, 2020
Reviewers invited
Invitations sent on 11 Dec, 2020
Editor assigned
On 11 Dec, 2020
Editor invited
On 11 Dec, 2020
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On 11 Dec, 2020
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On 01 Dec, 2020
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A new preprint design is coming!
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This preprint is under consideration at Scientific Reports. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research Article
Intikhab Alam
King Abdullah University of Science and Technology
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Under Review
Version 1
Posted 14 Dec, 2020
No community comments so far
Editorial decision: Major revision
On 02 Feb, 2021
Reviews received
Received 26 Jan, 2021
Reviewers agreed
On 24 Jan, 2021
Reviews received
Received 22 Jan, 2021
Reviewers agreed
On 14 Dec, 2020
Reviewers agreed
On 11 Dec, 2020
Reviewers invited
Invitations sent on 11 Dec, 2020
Editor assigned
On 11 Dec, 2020
Editor invited
On 11 Dec, 2020
Submission checks complete
On 11 Dec, 2020
First submitted
On 01 Dec, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
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.
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