Open Source S/R Software for Linux

This is a library for creating and manipulating graphs with focus on speedy operations for large, sparse graphs.

ConDEnSE (Confidential Data Enabled Statistical Exploration) will be a web-based environment for statistical analysis of confidential data from various database sources, based on Plone and R, and using the Jackknife method of confidentiality protection.

This project contains the source code associated with the PLoS Computational Biology publication: "Differential Expression Analysis for Pathways". The paper text can be found here: http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002967

Set of tools for basic analysis of electrophysiological data. The Python classes show how to call OpenElectrophy functions and save data. The R library applies circular statistics to spike phase data and saves the best von Mises fit and the Rayleigh statistics on the disk. The wavelet coherence analysis is done in R by the package "sowas". Check the module R_coherence to see how we solved that problem. This packages may be useful for people who start using OpenElectrophy and circular statistics in R. If you find errors, please report them. The project is still in development, so in the future you'll get updates.

GEPETTO (GEne PrioriTization ExTended TOol) is an original open-source framework, distributed under the LGPL license, for gene selection and prioritization on a desktop computer that ensures confidentiality of personal data. It takes advantage of the data integration capabilities in the SM2PH-Central Framework(KD4v,MSV3d,BIRD,..), combined with in-house developed gene prioritization methods. It currently incorporates six prioritization modules, based on gene sequence, protein-protein interactions, gene expression, disease-causing probabilities, genomic context). GEPETTO is written in Java/Python and supported by an advanced modular architecture, which means that it can easily be modified and extended by the user, in order to include alternative scoring methods and new data sources. We intend to extend the system from gene-level to variant-level prioritization, by exploiting the variant data in the MSV3D database. Contact: bmhoan@gmail.com or walter.vincent.fr@gmail.com

Hoea is a python module for hierarchical ontology enrichment analysis, which facilitated GO (Gene Ontology)/KO (KEGG Orthology) enrichment analysis at any desktop.

Platform for parallel computation in the Amazon cloud, including machine learning ensembles written in R for computational biology and other areas of scientific research. Home to MR-Tandem, a hadoop-enabled fork of X!Tandem peptide search engine.

Open Metaheuristic (oMetah) is a library aimed at the conception and the rigourous testing of metaheuristics (i.e. genetic algorithms, simulated annealing, ...). The code design is separated in components : algorithms, problems and a test report generator

The RDXplorer is a computational tool for copy number variants (CNV) detection in whole human genome sequence data using read depth (RD) coverage. CNV detection is based on the Event-Wise Testing (EWT) algorithm recently published by our group.

TEACUP automates many aspects of running TCP performance experiments in a specially-constructed physical testbed. TEACUP enables repeatable testing of different TCP algorithms over a range of emulated network path conditions, bottleneck rate limits and bottleneck queuing disciplines. TEACUP utilises a text-based configuration file to define experiments as combinations of parameters specifying desired network path and end host conditions. When multiple values are provided (e.g. for TCP congestion control algorithm), an experiment is made up of multiple tests. For each experiment and test, TEACUP collects a range of data, such as tcpdump files of traffic seen or TCP stack information (e.g. using Web10G). TEACUP also collects a variety of metadata from the end hosts and bottleneck router, such as the actual OS/kernel version(s) used. TEACUP also provides some simple tools for analysing the results of experiments, such as plotting a flow's experienced RTT over time.

Java-based scientific graphics with support for Java, Groovy, MATLAB, Python, the R statistical environment, Scala and SciLab.

ncPRO-seq is a tool for annotation and profiling of ncRNAs from smallRNA sequencing data. It aims to interrogate and perform detailed analysis on small RNAs derived from annotated non-coding regions in miRBase, piRBase, Rfam and repeatMasker, and regions defined by users. The ncPRO pipeline also has a module to identify regions significantly enriched with short reads that can not be classified as known ncRNA families. ############# Docker version : download and run Dockerfile (go in "Files" section) ############# GitHub : https://github.com/jbrayet/ncpro-seq

vipR is a program to screen for sequence variants (SNPs, deletions) in sequence data generated by high-throughput-sequencing platforms. Information on this and other projects can be found on: http://www.altmann.eu