Bioinformatics

 

The Bioinformatics Platform can advise and provide support regarding the exploitation of your data or existing data, including the layout and valorisation of results and the compilation of publications.

The Platform can also develop original methods and tools specific to your needs, based on the R, python, perl, julia or GO languages.

Expertise:

  • Processing and analysis of “omic” data (transcriptomics, proteomics, genomics),
  • Advice on and application of statistical tests adapted to the sample size and type of distribution,
  • Graphic representations: vulcano plot, box plot, violine, heatmap, radar plot, ROC curves, survival curves, etc.,
  • Determination of pathways from lists of genes or genes associated with proteins,
  • Comparisons of lists of proteins, peptides, pathways, etc.,
  • Determination of biomarkers using PCA, SPLS, RFE,
  • For proteomics:

-Qualitative analyses: processing of DDA data: identification of proteins using different search engines (Mascot, Amanda, Morpheus, etc.).

-Quantitative analyses: processing of DIA data: large-scale quantification of peptides using a SWATH approach (Spectronaut).

Development of bioinformatics tools:

There are innumerable ways to process data and often appropriate tools do not exist. We can create tailor-made tools using the following programming languages:

-R: a language particularly well-suited to statistics and graphic representations.

-Python: a language that can be used in numerous contexts and is widely used by the scientific community. It has a specific library for biology.

-Perl: the most powerful language to extract text data. Perl is used in linguistics. This is a very useful language to automate repetitive tasks under Linux.

-Julia: a high-quality and high performance programming language for digital calculations. Created by MIT in 2012, this very recent language is nearing the C speed in calculation.

-Go: this language was developed by Google to replace C/C++. Particularly efficient in multithreading, this language also produces programs that are portable and simple to install by means of cross-compilation.

Around a hundred of these tools are available at: https://sites.google.com/site/fredsoftwares/home

Training:

  • Initiation in Julia language: we can provide initial training in Julia programming, such as during the Journées nationales du DEVeloppement Logiciel (National Software Development event) in 2017: http://devlog.cnrs.fr/jdev2017/t7.ap04
  • Training in the use of the tools we have developed so that you can use them independently.

Bibliography:

The tools we invent may be the subject of publications:

-Sorting protein lists with nwCompare: a simple and fast algorithm for n-way comparison of proteomic data files.

Pont F, Fournié JJ. Proteomics. 2010 Mar;10(5):1091-4.

-nwCompare and AutoCompare Softwares for Proteomics and Transcriptomics Data Mining – Application to the Exploration of Gene Expression Profiles of Aggressive Lymphomas,

Fréderic Pont, Marie Tosolini, Bernard Ycart and Jean-Jacques Fournié (2012).  Integrative Proteomics, Hon-Chiu Eastwood Leung (Ed.), ISBN: 978-953-51-0070-6, InTech, Available from:

http://www.intechopen.com/books/integrative-proteomics/nwcompare-and-autocompare-softwares-for-proteomics-and-transcriptomics-data-mining-application-to-th

Scientists can also publish new tools with their results, thus adding value to an article by making an original program available to the community.

Example :

AutoCompare SES : Large scale microarray profiling reveals four stages of immune escape in Non-Hodgkin Lymphomas. Marie Tosolini, Christelle Algans, Frédéric Pont, Bernard Ycart & Jean-Jacques Fournié. OncoImmunology. 2016.

DeepTIL : Assessment of tumor-infiltrating TCRVγ9Vδ2 γδ lymphocyte abundance by deconvolution of human cancers microarrays.

Marie Tosolini, Frédéric Pont, Mary Poupot, François Vergez, Marie-Laure Nicolau-Travers, David Vermijlen, Jean- Emmanuel Sarry, Francesco Dieli, Jean-Jacques Fournié . OncoImmunology , 2017 : 6;6(3).

>>Rates