Référentiel des outils installés sur la plateforme Migale

La liste des packages R installés sur la plateforme Migale est disponible ici.


cluster-3.0 (version 3.0 - 2013-05-24)
The open source clustering software available here implement the most commonly used clustering methods for gene expression data analysis. The clustering methods can be used in several ways.Cluster 3.0 provides a Graphical UserInterface to access to the clustering routines. It is available for Windows, Mac OS X, and Linux/Unix. Python users can access the clustering routines by using Pycluster, which is an extension module to Python. People that want to make use of the clustering algorithms in their own C, C++, or Fortran programs can download the source code of the C Clustering Library.
Usage : #cluster



CNVnator (version 0.3 - 2015-02-13)
CNVnator: an approach to discover, genotype, and characterize typical and atypical CNVs from family and population genome sequencing.
Usage : #cnvnator



COLONY (version 2.0.6.3 - 2017-05-02)
COLONY is a Fortran program written by Jinliang Wang. It implements a maximum likelihood method to assign sibship and parentage jointly, using individual multilocus genotypes at a number of codominant or dominant marker loci.



Commet (version https://github.com/pierrepeterlongo/commet/archive/master.zip - 2018-05-04)
COMMET (“COmpare Multiple METagenomes”) provides a global similarity overview between all datasets of a large metagenomic project. Directly from non-assembled reads, all against all comparisons are performed through an efficient indexing strategy. Then, results are stored as bit vectors, a compressed representation of read files, that can be used to further combine read subsets by common logical operations. Finally, COMMET computes a clusterization of metagenomic datasets, which is visualized by dendrogram and heatmaps.
Remarque : Citation: Nicollas Maillet, Guillaume Collet, Thomas Vannier, Dominique Lavenier, and Pierre Peterlongo. “COMMET: comparing and combining multiple metagenomic datasets” IEEE International Conference on Bioinformatics and Biomedicine (BIBM) 2014.
Usage : #Commet.py [-h] [--sge] [--one_vs_all] [-b] [-o] [-k K] [-t T] [-l L] [-n N] [-e E] [-m M] input_file



consed (version 22.0 - 2014-04-30)
Consed/Autofinish is a tool for viewing, editing, and finishing sequence assemblies created with phrap. Finishing capabilities include allowing the user to pick primers and templates, suggesting additional sequencing reactions to perform, and facilitating checking the accuracy of the assembly using digest and forward/reverse pair information.
Remarque : Voir aussi autofinishs (http://www.ncbi.nlm.nih.gov:80/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=11282977s)
Usage : #consed



cross_match (version 0.990329 - 2002-11-06)
Cross_Match uses the same algorithm as Swat but also allows the comparison of a pair of sequences to be constrained to bands of the Smith-Waterman matrix that surround one or more matching words in the sequences. This substantially increases speed for large-scale nucleotide sequence comparisons without compromising sensitivity.
Usage : #cross_match



cufflinks (version 2.2.0 - 2014-05-06)
Cufflinks assembles transcripts and estimates their abundances in RNA-Seq samples. It accepts aligned RNA-Seq reads and assembles the alignments into a parsimonious set of transcripts. Cufflinks then estimates the relative abundances of these transcripts based on how many reads support each one.
Usage : #cufflinks [options]*



dadi (version 1.7 - 2016-07-18)
Remarque : If you use ???a???i in your research, please cite RN Gutenkunst, RD Hernandez, SH Williamson, CD Bustamante "Inferring the joint demographic history of multiple populations from multidimensional SNP data" PLoS Genetics 5:e1000695 (2009).



DART (version 1.2.4 - 2018-01-09)
DART: a fast and accurate RNA-seq mapper with a divide and conquer strategy
Usage : #dart -i Index_Prefix -f [-f2 ]



debarcer (version 0.3.1 - 2017-03-21)
Debarcer (De-Barcoding and Error Correction) is a package for working withnext-gen sequencing data that contains molecular barcodes.As it stands, it supports targeted sequencing libraries generated bySimSenSeq, a method of creating multiplexed barcoded sequencing librariesusing PCR.
Usage : #runDebarcer.sh -u


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