IMG is a powerful community resource for the comparative analysis and annotation of microbial genome data.
Tutorial and training materials by OpenHelix
| The Integrated Microbial Genomes (IMG) comparative genomics system supports timely and comprehensive analysis of genomes across multiple domains of life. The tools available on IMG allow for the analysis of genomes, genes and functions, individually or comparatively from Archaea, bacteria, eukaryotes, viruses and plasmids. Here a researcher can explore organism information, genome statistics and viewers, phylogenetic distributions of genes and horizontally transferred genes. Functional information includes protein domain, orthology, enzyme and pathway information. Genome analyses include abundance profiles, function profiles, genome clustering and more. Analysis carts and MyIMG are additional powerful analysis tools available to aid your research. | |||||
You'll learn:
- to find a set of objects (genomes, genes, or functions)
- to analyze profiles of objects (either individually or comparatively)
- to compare genomes using abundance and function profiles and by clustering
- to use other important tools such as IMG analysis carts and MyIMG
- how to view genome project maps and metadata category information
More about the resource:
The Integrated Microbial Genomes (IMG) resource comparative genomics system is a data management platform for analyzing microbial genomes. sequenced by the Joint Genome Institute (JGI) of the US Department of Energy. IMG also integrates data from many other public information resources, such as the European Bioinformatics Institute (EBI), the Swiss Institute of Bioinformatics, the National Center for Biotechnology Information (NCBI), Pfam, and the Kyoto Encyclopedia of Genes and Genomes (KEGG).
Related tutorials
This tutorial is a part of the tutorial group IMG resources. You might find the other tutorials in the group interesting:
- Integrated Microbial Genomes with Microbiome samples (IMG/M): IMG/M provides tools for analyzing the functional capability of microbial communities based on their metagenome sequence
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