Référentiel des outils installés sur la plateforme Migale

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

cd-hit (version 4.6.1 - 2013-08-12)
CD-HIT stands for Cluster Database at High Identity with Tolerance. The program (cd-hit) takes a fasta format sequence database as input and produces a set of non-redundant (nr) representative sequences as output.
Remarque : Exemple d utilisation : cd-hit -n 5 -i /db/fasta/nr90/nr90.fsa -o nr80 -M 2048 -c 0.8 -u clstr.lastweek
Usage : #cd-hit [Options]

cd-hit-454 (version - - 2013-08-05)
The 454 pyrosequencing reads contains artificially duplicates, which might lead to misleading conclusions. cdhit-454 is a fast program to identify exact and nearly identical duplicates, the reads begin at the same position but may vary in length or bear mismatches. cdhit-454 can process a dataset in ~10 minutes. it also provides a consensus sequence for each group of duplicates.
Usage : #cd-hit-454

Circlator (version 1.5.3 - 2017-12-26)
Circlator will attempt to identify each circular sequence in an assembly and output a linearised version of it.
Usage : # circlator [options]

circos (version 0.64 - 2013-01-20)
Circos is a software package for visualizing data and information. Itvisualizes data in a circular layout — this makes Circos ideal for exploringrelationships between objects or positions. There are other reasons why acircular layout is advantageous, not the least being the fact that it isattractive.
Usage : #circos

clustal-omega (version 1.1.0 - 2012-07-17)
Clustal Omega is the latest addition to the Clustal family. It offers a significant increase in scalability over previous versions, allowing hundreds of thousands of sequences to be aligned in only a few hours. It will also make use of multiple processors, where present. In addition, the quality of alignments is superior to previous versions, as measured by a range of popular benchmarks.
Remarque : Citing Clustal:Sievers F, Wilm A, Dineen DG, Gibson TJ, Karplus K, Li W, Lopez R, McWilliam H, Remmert M, Söding J, Thompson JD, Higgins DG (2011). Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega. Mol Syst Biol 7.
Usage : #clustalo --help

clustalx (version 2.1 - 2013-12-29)
Multiple sequence alignment program. It provides an integrated environment for performing multiple sequence and profile alignments and analysing the results.
Usage : #clustalx (en mode graphique) ou clustalw2 (en mode ligne de commande)

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 - 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


Menu principal

by Dr. Radut