| Program |
URL |
Platforms |
Distribution |
Category |
Description |
| R |
http://www.r-project.org/ |
Unix, Macintosh, Windows |
Open source |
Statistics |
One of the most famous statistical packages. Many librairies,
including specific ones for the analysis of microarray data. |
| Statistics for Microarray Analysis |
http://www.stat.berkeley.edu/users/terry/zarray/Software/smacode.html |
R package |
Open source |
Microarray analysis |
|
| YASMA |
http://people.cryst.bbk.ac.uk/wernisch/yasma.html |
|
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| Bioconductor |
http://www.bioconductor.org/ |
R package |
Open source |
Biostatistics |
An open source and open development software project for the
analysis and comprehension of genomic data. |
| TIGR Microarray suite TM4 |
http://www.tigr.org/software/tm4/ |
Java or C++ for Windows |
Open source |
Microarrays |
The TM4 suite of tools consist of four major applications,
Microarray Data Manager (MADAM), TIGR_Spotfinder, Microarray Data
Analysis System(MIDAS), and Multiexperiment Viewer(MeV) |
| TIGR MIDAS |
http://www.tigr.org/software/tm4/midas.html |
Java |
Open source |
Normalization |
TIGR Microarray Data Analysis System (MIDAS) is a microarray data
quality filtering and normalization tool that allows raw experimental
data to be processed through various data normalizations, filters, and
transformations via a user-designed analysis pipeline. Currently
implemented normalization and data analysis algorithms include
total-intensity normalization, Lowess (Locfit) normalization, flip-dye
consistency checking, replicates analysis, intensity-dependent z-score
filtering (slice analysis), etc. |
| TIGR MeV |
http://www.tigr.org/software/tm4/mev.html |
Java |
Open source |
Clustering
Visualization |
TIGR MultiExperiment Viewer (MEV) is a Java application designed
to allow the analysis of microarray data to identify patterns of gene
expression and differentially expressed genes. Numerous normalization,
clustering and distance algorithms have been implemented, along with a
variety of graphical displays to best present the results. |
|
http://www.tigr.org/software/tm4/utilities.html |
Windows |
Freeware |
Converter utility |
ExpressConverter is a file format transformation tool that reads
GenePix file as input and generates output as TIGR ArrayView file
(.tav) or TIGR MultiExperiment Viewer file (.mev) so that the
microarray data can be uploaded to databases with MADAM and analyzed
with MIDAS and MEV. |
| BRB ArrayTools |
http://linus.nci.nih.gov/BRB-ArrayTools.html |
Windows + Excel |
Freeware |
|
BRB ArrayTools is an integrated package for the visualization and
statistical analysis of DNA microarray gene expression data. It was
developed by professional statisticians experienced in the analysis of
microarray data and involved in the development of improved methods
for the design and analysis of microarray based experiments. The array
tools package utilizes an Excel front end. Scientists are familiar
with Excel and utilizing Excel as the front end makes the system
portable and not tied to any database. The input data is assumed to be
in the form of Excel spreadsheets describing the expression values and
a spreadsheet providing user-specified phenotypes for the samples
arrayed. The analytic and visualization tools are integrated into
Excel as an add-in. The analytic and visualization tools themselves
are developed in the powerful R statistical system, in C and Fortran
programs and in Java applications. Visual Basic for Applications is
the glue that integrates the components and hides the complexity of
the analytic methods from the user. The system incorporates a variety
of powerful analytic and visualization tools developed specifically
for microarray data analysis.
|
| ViDaExpert |
http://www.ihes.fr/~zinovyev/vida/vidaexpert.htm |
Windows |
Freeware |
Vizualisation |
Software tool for visualization of multidimensional datasets. It
allows to make understandable color illustrations of a dataset to
explore it’s intrinsic patterns and regularities. The main technique
implemented in ViDaExpert is the Method of Elastic Maps – advanced
analogue of the Method of Self-Organizing Maps. Besides, there are
many other methods of data analysis, including Principal Components
Analysis, different clustering methods, Linear Discriminate Analysis,
Linear Regression Method. |
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| Program |
URL |
Description |
| BASE |
http://base.thep.lu.se |
|
| SNOMAD - Standardization and NOrmalization of MicroArray Data |
http://pevsnerlab.kennedykrieger.org/snomadinput.html |
SNOMAD consists of a collection of algorithms directed at the
normalization and standardization of DNA microarray data. The
majority of the transformations within SNOMAD are directed at the
refinement of paired microarray data ... |
| INCLUSive: A web portal and service registry
for microarray and regulatory sequence analysis |
http://www.esat.kuleuven.ac.be/inclusive |
INCLUSive is a suite of algorithms and tools for the analysis of
gene expression data and the discovery of cis-regulatory sequence
elements. The tools allow normalization, filtering and clustering of
microarray data, functional scoring of gene clusters, sequence
retrieval, and detection of known and unknown regulatory elements
using probabilistic sequence models and Gibbs sampling. |
| GEPAS: A web-based resource for microarray gene expression data analysis. |
http://www.gepas.org/ |
GEPAS is composed of different interconnected modules which
include tools for data pre-processing, two-conditions comparison,
unsupervised and supervised clustering (which include some of the most
popular methods as well as home made algorithms) and several tests for
differential gene expression among different classes, continuous
variables or survival analysis. A multiple purpose tool for data
mining, based on Gene Ontology, is also linked to the tools, which
constitutes a very convenient way of analysing clustering
results. |
| GEDA |
http://bioinformatics.upmc.edu/GE2/GEDA.html |
GEDA provides a large number of options for
transformation and normalization as well as a diversity of tests for
finding differentially expressed genes.ÊÊ All of the tests can be
performed in combination with a variety of clustering algorithms for
class prediction. Extensive data quality metrics and graphical outputs
are included in the output, including M-A plots, mean vs. variance
plots, mean group correlation plots, box and whisker plots Êa gene
expression pattern grid.ÊÊ Computational valdiation options include
cross-fold validation, leave-one-out validation, and bootstrapping.ÊÊ
A variety of published cancer microarray data sets are available for
analysis on-tap.
|
| GenePublisher: Automated analysis of DNA microarray data. |
http://www.cbs.dtu.dk/services/GenePublisher |
The server performs normalization, statistical analysis and
visualization of the data. The results are run against databases of
signal transduction pathways, metabolic pathways and promoter
sequences in order to extract more information. |
| ExpressYourself: A modular platform for processing and visualizing microarray data. |
http://bioinfo.mbb.yale.edu/expressyourself |
In completely automated fashion, it will correct the background
array signal, normalize the Cy5 and Cy3 signals, score levels of
differential hybridization, combine the results of replicate
experiments, filter problematic regions of the array and assess the
quality of individual and replicate experiments. ExpressYourself is
designed with a highly modular architecture so various types of
microarray analysis algorithms can readily be incorporated as they are
developed; for example, the system currently implements several
normalization methods, including those that simultaneously consider
signal intensity and slide location. |
| REDUCE: An online tool for inferring
cis-regulatory elements and transcriptional module activities from
microarray data. |
http://bussemaker.bio.columbia.edu/reduce/ |
REDUCE is a motif-based regression method for microarray
analysis. The only required inputs are (i) a single genome-wide set of
absolute or relative mRNA abundances and (ii) the DNA sequence of the
regulatory region associated with each gene that is probed. Currently
supported organisms are yeast, worm and fly; it is an open question
whether in its current incarnation our approach can be used for mouse
or human. REDUCE uses unbiased statistics to identify oligonucleotide
motifs whose occurrence in the regulatory region of a gene correlates
with the level of mRNA expression. Regression analysis is used to
infer the activity of the transcriptional module associated with each
motif. |
| ChipInfo: Software for extracting gene annotation and gene ontology information for microarray analysis. |
http://biosun1.harvard.edu/complab/chipinfo/ |
To date, assembling comprehensive annotation information for all
probe sets of any Affymetrix microarrays remains a time-consuming,
error-prone and challenging task. ChipInfo is designed for retrieving
annotation information from online databases such as NetAffx and Gene
Ontology and organizing such information into easily interpretable
tabular format outputs. As companion software to dChip and GoSurfer,
ChipInfo enables users to independently update the information
resource files of these software packages. It also has functions for
computing related summary statistics of probe sets and Gene Ontology
terms. |
| Regulatory sequence analysis tools. |
http://rsat.ulb.ac.be/rsat/ |
A collection of software tools dedicated to the prediction of
regulatory sites in non-coding DNA sequences. These tools include
sequence retrieval, pattern discovery, pattern matching, genome-scale
pattern matching, feature-map drawing, random sequence generation and
other utilities. Alternative formats are supported for the
representation of regulatory motifs (strings or position-specific
scoring matrices) and several algorithms are proposed for pattern
discovery. |
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