Analyse transcriptome


VersionMAJ

AnovArray

1.12003-10-20DownloadDoc
AnovArray permet la quantification des facteurs biologiques et des biais techniques, ainsi que l'identification des gènes différentiellement exprimés entre plusieurs conditions expérimentales (deux et plus) pour des expériences transcriptomiques issues de macroarray et microarray dans la cadre d'un plan d'expérience factoriel équilibré et d'un modèle complet. Ce package est développé en SAS (logiciel statistique) et bénéficie en conséquence de toutes les procédures statistiques de ce logiciel. Les méthodes statistiques dans ce package sont l'analyse de la variance (ANOVA) et les tests multiples de type FDR (False Discovery Rate).

Remarque
Run Unix # Utilisation sous SASRun Web #

VersionMAJ

base

1.2.122004-08-12DownloadDoc
BioArray Software Environment (BASE) est une base de données permettant de gérer l’importante quantité de données générées par des analyses de bio-puces. BASE gère les informations biologiques, les données brutes et les images. BASE possède également des outils de normalisation, de visualisation et d’analyse des données.

Remarque
Run Unix # Run Web # http://genome.jouy.inra.fr/basejouy

VersionMAJ

class2g

1.02006-04-04DownloadDoc
Class2G permet de classer les gènes en deux groupes en utilisant un modèle de mélange. Les principales caractéristiques sont d'une part l'affectation des gènes est associée à une probabilité, et d'autre part l'analyse d'un macroarray est indépendante d'une référence. Class2G est intégrée au système BASE (BioArray Software Environment) par l'intermédiaire d'un plug-in perl, et est développé dans l'environnement statistique R. BASE permet d'accéder à une interface web conviviale, d'utiliser un seul environnement pour le stockage et l'analyse de données. Class2G a été utilisé pour la détection de gènes présents et absents de E. faecalis dans le cadre de l'analyse d'une trentaine de macroarray (P.Serror - INRA Jouy-en-Josas - UBLO).

Remarque
Run Unix # Run Web # http://genome.jouy.inra.fr/basejouy

VersionMAJ

cluster-3.0

3.02013-05-24DownloadDoc
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 User Interface 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.

Remarque
Run Unix # clusterRun Web #

VersionMAJ

cufflinks

2.2.02014-05-06DownloadDoc
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.

Remarque
Run Unix # cufflinks [options]* Run Web #

VersionMAJ

geneclust

1-0.02007-03-27DownloadDoc
GeneClust is a piece of computer software which can be used as a tool for exploratory analysis of gene expression microarray data. The development of GeneClust was motivated by surging interest to search for interpretable biological structure in gene expression microarray data.

Remarque
Run Unix # geneclustRun Web #

VersionMAJ

matrix2png

1.2.12011-05-30DownloadDoc
Matrix2png is a simple but powerful program for making visualizations of microarray data and many other data types. It generates PNG formatted images from text files of data. It is fast, easy to use, and reasonably flexible. It can be used to generate publication-quality images, or to act as a image generator for web applications. Our group has found it useful for imaging all kinds of matrix-based data, not just microarray data.

Remarque If you use images created with matrix2png for publication or presentation, please cite:Pavlidis, P. and Noble W.S. (2003) Matrix2png: A Utility for Visualizing Matrix Data. Bioinformatics 19: 295-296 (abstract).Readers of the Bioinformatics application note: Here is the color version of the figure from the paper (pdf format).
Run Unix # matrix2pngRun Web #

VersionMAJ

miranda

3.3a2014-10-29DownloadDoc
miRanda is an algorithm for the detection of potential microRNA target sites in genomic sequences. miRanda reads RNA sequences (such as microRNAs) from file1 and genomic DNA/RNA sequences from file2. Both of these files should be in FASTA format.

Remarque
Run Unix # miranda file1 file2 [options..]Run Web #

VersionMAJ

nupack

3.02010-12-01DownloadDoc
NUPACK is a growing software suite for the analysis and design of nucleic acid systems. The package currently enables thermodynamic analysis of dilute solutions of interacting nucleic acid strands, and sequence design for complexes of nucleic acid strands intended to adopt a target secondary structure at equilibrium. NUPACK algorithms are formulated in terms of nucleic acid secondary structure. In most cases, pseudo-knots are excluded from the structural ensemble. Much of this software may be conveniently run through the NUPACK web server at http://www.nupack.org (Zadeh et al., 2010b).

Remarque
Run Unix # Run Web #

VersionMAJ

StringTie

1.3.02016-09-07DownloadDoc
StringTie is a fast and highly efficient assembler of RNA-Seq alignments into potential transcripts. It uses a novel network flow algorithm as well as an optional de novo assembly step to assemble and quantitate full-length transcripts representing multiple splice variants for each gene locus. Its input can include not only the alignments of raw reads used by other transcript assemblers, but also alignments longer sequences that have been assembled from those reads.In order to identify differentially expressed genes between experiments, StringTie's output can be processed by specialized software like Ballgown, Cuffdiff or other programs (DESeq2, edgeR, etc.).

Remarque
Run Unix # stringtie -h/--helpRun Web #

VersionMAJ

xdigitise

3.5.102002-04-19DownloadDoc
Evaluation d experience d hybridation

Remarque
Run Unix # xdigitiseRun Web #

Menu principal

Page | by Dr. Radut