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Integrative visualization of multiple omic datasets onto KEGG pathways.

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Paintomics, integrative visualization of multiple omic data

THIS PROJECT IS NOT SUPPORTED ANYMORE.

You can find the latest sources in brach main

For any question on PaintOmics 3, users can send a mail to [email protected].

PaintOmics 3 official instance: https://bioinfo.cipf.es/paintomics/

Welcome to PaintOmics 3 documentation.

Note: this documentation is temporal, we still developing the tool and we'll fill this documentation as soon as we release a first version.

Anyway, a short description of the application...

PaintOmics 3 is a web tool for the integrative visualization of multiple omic datasets onto KEGG pathways.

PaintOmics 3 consists of three simple steps:

  • Data uploading: typically data matrices, containing, for example, gene expression, metabolite levels and metabolite levels for the same set of samples.
  • Identifier and Name Matching and Metabolite assignment: as Paintomics requires Entrez IDs for working with KEGG pathways, the tool will try to convert the names and identifiers from different sources and databases for the input data. Additionally, it's necessary to specify of metabolite assignments in ambiguity cases.
  • Pathway selection: finally, Paintomics will obtain the list of KEGG Pathway that are ?.

Currently PaintOmics 3 supports integrated visualization of multipel species of different biological kingdoms and offers user the possibility to request any other organism present in the KEGG database.

PaintOmics 3 application is distributed under GNU General Public License, Version 3.

Paintomics v3.0 is part of the STATegra Project and was developed by the Genomics of Gene Expression Lab at Príncipe Felipe Research Centre.

Contact

** Rafael Hernández de Diego **, Main Developer.

** Ana Conesa, PhD. **, Head Genomics of Gene Expression Lab.

For any question on STATegraEMS, users can send a mail to [email protected].

TODO list

https://trello.com/b/58vOjrpW/paintomics-3-todos

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Integrative visualization of multiple omic datasets onto KEGG pathways.

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