COLOMBOS
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| Link/URL: | |
|---|---|
| What: |
COLlection Of Microarrays for Bacterial OrganismS Gene expression for E. coli and other model bacteria |
| Who: |
Kristof Engelen et al. Department of Computational Biology, Fondazione Edmund Mach, San Michele all'Adige, Trento, Italy |
| Updates: | |
| Upcoming events: | |
| Web Services: |
REST services available |
| edit table |
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Contents
About COLOMBOS
COLOMBOS[1] is a collection of expression data from published microarrays and RNAseq for E. coli, among many other prokaryotes. COLOMBOS combines expression analysis across data from different papers, labs, and platforms. A key idea in COLOMBOS is to compare relative expression values to a reference state as sets of "condition contrasts". This should correct for platform-dependent differences between studies. The expression data contained within the database have also been linked to a manually curated, standardized condition annotation and ontology created specifically for the COLOMBOS compendia. Uniquely, it also allows analysis expression data for all species simultaneously, and identification candidate genes with evolutionary conserved expression behaviour.
Content
As of the most recent update published in NAR [2], COLOMBOS coverage of E. coli expression data included 5510 microarray or RNAseq samples from 254 experiments.
It also features large expression compendia for Salmonella enterica, Bacillus subtilis, Bacillus anthracis, Bacillus cereus, Streptomyces coelicolor, Pseudomonas aeruginosa, Mycobacterium tuberculosis, Helicobacter pylori, Bacteroides thetaiotaomicron, Campylobacter jejuni, Clostridium acetobutylicum, Lactobacillus rhamnosus, Methanococcus maripaludis, Shigella flexneri, Sinorhizobium meliloti, Streptococcus pneumoniae, Thermus thermophilus and Yersinia pestis.
Using COLOMBOS
Key vocabulary:
- contrast: the difference between a test and reference condition in a particular experiment
- module: saved results of searches for genes, contrasts, or genes and contrasts.
COLOMBOS provides a kind of online workbench where you can create modules by giving lists of genes, experiments, or both. These modules can then be visualized and manipulated in various ways. Common operations include starting from a set of known genes to find the conditions where they are (co)-expressed or to identify additional co-expressed genes.
The COLOMBOS expression compendia are also available for download in their entirety for application of stand-alone tools for use within the greater scope of systems biology.
Usage examples
Add links to additional pages describing success stories here.
E. coli-centric expression databases
General repositories
Technology
The COLOMBOS web access portal is currently built using Ext JS java script libraries supported by PHP and Matlab back-end scripts to interact with the database.
REST services
The COLOMBOS database can be programmatically accessed and queried through a REST web service, so that external resources can include COLOMBOS expression data in reports that they generate for their users. This REST web service contains an API with several functions to list and query the database content. The output of these operations is provided in JSON format to allow other web resources to integrate the results into their own site. More information on the options and usage of this web service can be found within the help documentation on the COLOMBOS website.
R package
As an example for the feasibility of programmatic access to the data through the REST API, a COLOMBOS R package is available, which can be found on CRAN. This R package allows users to perform complex queries to the COLOMBOS database from within the R statistical environment and take advantage of the collection of R packages to perform further statistical analysis and visualizations.
Direct module creation link
A module can be directly created within the web portal through a PHP GET query. This query allows users to define their organism and their genes of interest. Using this link will immediately start up a 'quick search' to build a module with the entered options.
This query can be adjusted by changing the organism alias after 'org=' and adding your genes of interest as locus tags or common names separated by a comma after 'genes='.
Discussion
References
See Help:References for how to manage references in EcoliWiki.
