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Welcome to the Babelomics wiki!
Babelomics is an integrative platform for the analysis of Transcriptomics, Proteomics and Genomics data with advanced functional profiling. This new version of Babelomics integrates primary (normalization, calls, etc.) and secondary (signatures, predictors, associations, TDTs, clustering, etc.) analysis tools within an environment that allows relating genomic data and/or interpreting them by means of different functional enrichment or gene set methods. Such interpretation is made using functional definitions, protein-protein interactions...
Babelomics has been extensively re-engineered and now it includes the use of web services and HMTL5 technology features, a new user interface with persistent sessions and a new extended database of gene identifiers. Babelomics is available at http://www.babelomics.org
Some rationale about the name...
This resource is named after the tale The Babel library, by the famous Argentinean writer Jorge Luis Borges. In the tale an infinite library is described:
"The universe (which others call the Library) is composed of an indefinite and perhaps infinite number of hexagonal galleries... There are five shelves for each of the hexagon's walls; each shelf contains thirty-five books of uniform format; each book is of four hundred and ten pages; each page, of forty lines, each line, of some eighty letters which are black in color."
Such infinite library would contain any possible book, but also infinite non-sense combinations of letters. Finding the real books among the pile of meaningless texts is an excellent metaphor of the challenge that constitutes the extraction information out of the flood of data in the post-genomic era. Babelomics offers different procedures to manage, analyze and interpret genomic data within the proper statistical frame.
The general pipeline of the Babelomics main working areas can be easily visualized in this graphic:
Processing. You can find in this menu all tools for data preprocessing (transformations, missing value imputation, merging replicates...), microarray and RNA-seq normalization. From here you can edit variables for your uploaded data.
Expression. Under this section you will find the tools for gene expression analysis as differential gene expression (RNA-Seq and microarrays data), supervised and unsupervised analysis (class discovery and clustering).
Genomics. Tools to analyze SNP data from GWAS (Genome-Wide Association Studies) and TDTs. Also there is an approach in association studies when using sequence data.
Cancer. Two different approaches to analyse cancer genomic sequences.
Functional. Different options for the functional interpretation of the genomic data previously analyzed in the above sections.
In the tutorial you will learn how to use Babelomics. Tutorial covers main functionalities such as:
- User interface functionality.
- Creating an account.
- WEB forms: inputs, steps and outputs.
Frequently asked questions
You can browse the most typical questions FAQ.
Requirements. What do you need for using Babelomics 5.0?
Software and databases used. Here you will find information about the software and databases that have been used for building Babelomics.
To report an error or suggestion, please contact us at: firstname.lastname@example.org
If you are using Babelomics in training activities, we would like to know to provide additional documentation, exercises and other information of interest for you.
Alonso R, Salavert F, Garcia-Garcia F, Carbonell-Caballero J, Bleda M, Garcia-Alonso L, Sanchis-Juan A, Perez-Gil D, Marin-Garcia P, Sanchez R, Cubuk C, Hidalgo MR, Amadoz A, Hernansaiz-Ballesteros RD, Alemán A, Tarraga J, Montaner D, Medina I and Dopazo J. Babelomics 5.0: functional interpretation for new generations of genomic data. Nucl. Acids Res. (2015) 43 (W1): W117-W121. doi: doi: 10.1093/nar/gkv384 - NAR - PubMed - Google Scholar