What is Manteia?
What are the affymetrix arrays and probe sets used in Manteia?
How to compute statistics for microarrays that are not listed in Manteia?
How do I download data from Manteia?
What is the purpose of the login button?
How to contact us?
How to cite Manteia?
Who can use Manteia?
How often Manteia is updated?
Where do the data used in Manteia originate from?
Disclaimer

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What is Manteia?
Manteia is an integrative database which provides a large array of data related to the embryonic development of the mouse, chicken, zebrafish and man. Data include phenotypes, diseases, functional annotations, expression data, gene regulation, genetic data, phylogenies, interactomes, etc. from various public databases. These data are processed so they can be compared and used together across species.

Manteia offers tools to explore each type of data independently but also to combine them in order to answer complex biological questions and to test hypotheses. This can be done using the interface or a query language. For example, an investigator could use Manteia to search for transcription factors responsible for a muscle phenotype in the mouse and transcribed from a given area of a chromosome and then evaluate the likelihood that these transcription factors are related to a disease in humans by combining genomic, phenotype, disease and orthology data.

Results can be visualized as text or using dynamic interactive graphs. Lists of genes can be analyzed statistically to highlight the features they share. Similarly, features can be analyzed to see how well they are correlated. It allows one to see, for example, if a disease or its phenotypic features are associated with a given biological pathway.

This system could be extremely helpful to understanding the etiologies of genetic diseases. To this end, we have implemented an entity-quality method in Manteia, which is designed to automatically provide candidate genes from animal models based on the OMIM description of human diseases. We have further enhanced this approach by giving the user the option of using their own evidences and data in the query (linkage analysis, high throughput experiment data, etc.).

Learn more about Manteia on Facebook: https://www.facebook.com/Manteia.research

What are the affymetrix arrays and probe sets used in Manteia?
The microarrays used in Manteia are the Human Genome U133 Plus 2.0 Array, the Mouse Genome 430 2.0 Array, the Mouse MoGene 1.0st, the Chicken Array and the Zebrafish Array.

How to compute statistics for microarrays that are not listed in Manteia?
You can analyze every kind of array as long as you know which genes correspond to your probe sets. You can figure this out using the annotation file corresponding to your array (e.g for affy: http://www.affymetrix.com/estore/support/technical/annotationfilesmain.affx).
copy/paste one (or several) column containing identifiers (for the entire array) that are compatible with manteia in http://manteia.igbmc.fr/ID.php (e.g. ensembl gene id, swissprot, refseq...). Don't forget to select the right species and the type of identifier you are using on this page. Press submit, then go to the bottom of the page, select "create custom ref for statistics" in the refine menu. Press the refine button.
In the next page, Enter a name for your array, select the type of annotation you want to analyze (e.g. GO, phenotype...), press submit. You have created your reference array in manteia. It will be available as long as you keep a manteia page open.
Now select the genes corresponding to the dataset you want to analyze. obviously, this dataset has to be part of the array. Again, enter the gene identifiers in http://manteia.igbmc.fr/ID.php then press submit. Go to the bottom of the page. Select "GO stat" in the first statistics menu, then your custom array name in the second menu. Press statistics. This will compute your data.

How do I download data from Manteia?
You can download the annotation corresponding to a list of genes by selecting "export annotation" in the Refine drop down menu. Then press Refine and select the type of feature you want to export in the next menu. The file you get is tabulated and can be used in a text editor or a spreadsheet software like Microsoft Excel.

What is the purpose of the login button?
This button allows our team to test new tools and data with the current version of the system before their official release.

How to contact us?
Please send your questions and comments to otassy@igbmc.fr

How to cite Manteia?
If you use Manteia for your work, please cite:
Manteia, a predictive data mining system for vertebrate genes and its applications to human genetic diseases. Olivier Tassy; Olivier Pourquie. Nucleic Acids Research 2013
The article is freely available here:
https://dx.doi.org/10.1093%2Fnar%2Fgkt807

If you used the machine learning tool (Lookalike), please cite:
New data and features for advanced data mining in Manteia. Olivier Tassy. Nucleic Acids Research 2017 Jan 4;45(D1):D707-D711.
The article is freely available here:
https://dx.doi.org/10.1093%2Fnar%2Fgkw999

Who can use Manteia?
Manteia is a public resource, free of charge to use for academic purposes. We just ask you to cite Manteia in your work and publications. We also value your feedback to make the system better.

How often Manteia is updated?
We update the database once a year or whenever a major new release of a genome is made available.

Where do the data used in Manteia originate from?
Manteia combines data and ontologies from various public databases including:
Ensembl, NCBI, MGI, ZFIN, Inparanoid, Compara, Gene ontology, Interpro, DBD, reactome, ENCODE, Embrys, Unigene, Affymetrix, Mammalian Phenotype Ontology, Human Phenotype Ontology, PATO, FMA, MA and UBERON.

Disclaimer
External programs, data, logos and trademarks are copyrighted by and are the property of their respective owners.

Dynamic graphs are computed using the D3 library.
Gene radars are adapted from Peter Cook's chart.
Tree maps are adapted from Bill White's chart.

some illustrations are provided by psdgraphics and morguefile.

The Manteia system, data and analyses are provided "as is" with no warranties, expressed or implied as to capabilities or accuracy. User assumes the entire risk as to the results and performance of the software, data and documentation



 
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