Key Analytical & Database Resources & References for Agricultural Microbiomes
Microbiome research data, standards, and database resources
Resource/platform/tool | Website | Description |
---|---|---|
iMicrobe |
Data-sharing platform and bioinformatics tools that generate datasets that can be sent to a variety of 'omics-related apps that deliver data products and visualizations |
|
Cyverse |
Provides powerful computational infrastructure to handle huge datasets and complex analyses, including data storage, bioinformatics tools, image analyses, cloud services, APIs, and more. |
|
Genomic Standards Consortium (GSC) |
Enables genomic data integration, discovery and comparison through international community-driven standards |
|
National microbiome data collaborative (NMDC) |
Standardized data processing and management, data integration and distribution across partnering organizations |
|
iTagger |
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Pipeline for processing Illumina amplicon libraries (using USEARCH and QIIME). All samples to be compared should be identically constructed, sequenced, and analyzed. It facilitates analysis of large numbers of samples. |
National Center for Biotechnology Information |
Repository of raw sequence data |
|
MG-RAST |
Metagenomics analysis server and repository |
|
International Metagenomics and Microbiomes Standards Alliance (IMMSA) |
Identify standards and reference materials that currently exists or are being developed |
|
Integrated Microbial Genomes and metagenomes (IMG/M) |
Comprehensive integrated repository of sequence data with metadata, and analysis system |
|
Microbiomes in Transition Initiative (MinT) |
Coordinates state-of-the-art research to address key knowledge gaps in microbiome understanding. Use computational biology, bioinformatics, and statistics to develop new approaches to analyze large microbiome datasets, and to build models to capture and predict their behavior. |
|
Department of Energy Systems Biology Knowledgebase (KBase) |
Open-source software and data platform that enables users to upload their own data, analyze it (along with collaborator and public data), build realistic models, and share and publish their workflows and conclusions. Analytical capabilities include (meta)genome assembly, annotation, comparative genomics, transcriptomics, and metabolic modeling. |
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G.E.M.STM |
Data sharing and analysis platform to enable public-private research collaborations for innovation in agricultural production and other domain areas |
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Ag Data Commons |
Provides access to a wide variety of open data relevant to agricultural research and related domains |