TriCluster / MicroCluster – Microarray Gene Expression Clustering

TriCluster / MicroCluster

:: DESCRIPTION

Tricluster is the first tri-clustering algorithm for microarray expression clustering. It builds upon the new microCluster bi-clustering approach. Tricluster first mines all the bi-clusters across the gene-sample slices, and then it extends these into tri-clusters across time or space (depending on the third dimension). It can find both scaling and shifting patterns

MicroCluster is a deterministic biclustering algorithm that can mine arbitrarily positioned and overlapping clusters of gene expression data to find interesting patterns

::DEVELOPER

Mohammed J. Zaki

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • C++ Compiler

:: DOWNLOAD

 TriCluster / MicroCluster

:: MORE INFORMATION

Citation

Lizhuang Zhao and Mohammed J. Zaki,
TriCluster: An Effective Algorithm for Mining Coherent Clusters in 3D Microarray Data.
In ACM SIGMOD Conference on Management of Data. Jun 2005.

Lizhuang Zhao and Mohammed J. Zaki,
MicroCluster: An Efficient Deterministic Biclustering Algorithm for Microarray Data.
IEEE Intelligent Systems, 20(6):40-49. Nov/Dec 2005

PathVar – Microarray Analysis of Pathway Expression Variance

PathVar

:: DESCRIPTION

PathVar is a new dedicated web application to analyze these data sources. The software ranks pathway-representing gene/protein sets in terms of the differences of the variance in the within-pathway expression levels across different biological conditions.

::DEVELOPER

PathVar team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Bioinformatics. 2012 Feb 1;28(3):446-7. doi: 10.1093/bioinformatics/btr656. Epub 2011 Nov 28.
PathVar: analysis of gene and protein expression variance in cellular pathways using microarray data.
Glaab E, Schneider R.

GeneAnnot 2.2 – Microarray Gene Annotation

GeneAnnot 2.2

:: DESCRIPTION

The GeneAnnot system explores the many-to-many relationship between probe-sets and genes, by directly comparing the individual probe sequences with publicly available cDNAs and predicted genes from GenBank, RefSeq and Ensembl. The transcript sequences are further identified as GeneCards genes using the GeneLoc system which merges LocusLink and Ensembl gene indices on the basis of their genomic position.

::DEVELOPER

GeneAnnot team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation:

BMC Bioinformatics. 2007 Nov 15;8:446.
Novel definition files for human GeneChips based on GeneAnnot.
Ferrari F1, Bortoluzzi S, Coppe A, Sirota A, Safran M, Shmoish M, Ferrari S, Lancet D, Danieli GA, Bicciato S.

Bioinformatics. 2004 Jun 12;20(9):1457-8. Epub 2004 Feb 12.
GeneAnnot: comprehensive two-way linking between oligonucleotide array probesets and GeneCards genes.
Chalifa-Caspi V, Yanai I, Ophir R, Rosen N, Shmoish M, Benjamin-Rodrig H, Shklar M, Stein TI, Shmueli O, Safran M, Lancet D.

MIRACLE 1.0.2 / Rmiracle – Microarray R-based Analysis of Complex Lysate Experiments

MIRACLE 1.0.2/ Rmiracle

:: DESCRIPTION

MIRACLE is a web-application for handling reverse phase protein array chips

RmiracleR package for analysis of reverse phase protein array data in conjunction with MIRACLE.

::DEVELOPER

Baumbach lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 MIRACLE , Rmiracle

:: MORE INFORMATION

Citation:

Microarray R-based analysis of complex lysate experiments with MIRACLE.
List M, Block I, Pedersen ML, Christiansen H, Schmidt S, Thomassen M, Tan Q, Baumbach J, Mollenhauer J.
Bioinformatics. 2014 Sep 1;30(17):i631-i638.

CAFE 1.22.0 – Detection of Gross Chromosomal Abnormalities from Gene Expression Microarray data

CAFE 1.22.0

:: DESCRIPTION

CAFE (Chromosomal Aberration Finder in Expression data) is an R package for the detection of gross chromosomal gains and losses from expression microarrays, with a resolution up to cytoband level.

::DEVELOPER

Computational Biology and Data Mining (CBDM) Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/ windows/MacOsX
  • R
  • BioConductor

:: DOWNLOAD

  CAFE

:: MORE INFORMATION

Citation

Bioinformatics. 2014 May 15;30(10):1484-5. doi: 10.1093/bioinformatics/btu028. Epub 2014 Jan 21.
CAFE: an R package for the detection of gross chromosomal abnormalities from gene expression microarray data.
Bollen S1, Leddin M, Andrade-Navarro MA, Mah N.

maSigPro 1.58.0 – R package for the analysis of Microarray and RNA-seq Time Series data

maSigPro 1.58.0

:: DESCRIPTION

maSigPro (MicroArray Significant Profiles)is a regression based approach to find genes for which there are significant gene expression profile differences between experimental groups in time course microarray experiments.

::DEVELOPER

The Genomics of Gene Expression Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/Windows/MacOsX
  • R Package
  • BioConductor

:: DOWNLOAD

 maSigPro

:: MORE INFORMATION

Citation

Next maSigPro: updating maSigPro Bioconductor package for RNA-seq time series.
Nueda MJ, Tarazona S, Conesa A.
Bioinformatics. 2014 Jun 3. pii: btu333.

Bioinformatics. 2006 May 1;22(9):1096-102. Epub 2006 Feb 15.
maSigPro: a method to identify significantly differential expression profiles in time-course microarray experiments.
Conesa A1, Nueda MJ, Ferrer A, Talón M.

Mayday 2.14 – Microarray Data Analysis

Mayday 2.14

:: DESCRIPTION

Mayday (Microarray Data Analysis)is a workbench for visualization, analysis and storage of microarray data.

Mayday offers a variety of plug-ins, such as various interactive viewers, a connection to the R statistical environment, a connection to SQL-based databases, and different clustering methods, including phylogenetic methods.

In addition, so-called meta information objects are provided for annotation of the microarray data allowing integration of data from different sources. This meta information can be used to enhance visualizations, such as in the enhanced heatmap visualization.

::DEVELOPER

Research Group “Integrative Transcriptomics” , Center for Bioinformatics Tübingen, University of Tübingen

:: SCREENSHOTS

:: REQUIREMENTS

:: DOWNLOAD

Mayday

:: MORE INFORMATION

Citation

Florian Battke, Stephan Symons and Kay Nieselt: Mayday – Integrative analytics for expression data;
BMC Bioinformatics 11 (1):121 (2010)

CalMaTe 0.12.1 – Improved Allele-Specific Copy Number of SNP Microarrays for Downstream Segmentation

CalMaTe 0.12.1

:: DESCRIPTION

CalMaTe is a multi-array post-processing method of allele-specific copy-number estimates (ASCNs).

::DEVELOPER

Henrik Bengtsson <henrikb at braju.com>

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux/ MacOsX
  • R

:: DOWNLOAD

 CalMaTe

:: MORE INFORMATION

Citation

Bioinformatics. 2012 Jul 1;28(13):1793-4. doi: 10.1093/bioinformatics/bts248. Epub 2012 May 9.
CalMaTe: a method and software to improve allele-specific copy number of SNP arrays for downstream segmentation.
Ortiz-Estevez M1, Aramburu A, Bengtsson H, Neuvial P, Rubio A.

Array Designer 4.43 – Oligo & cDNA Microarray Design Software

Array Designer 4.43

:: DESCRIPTION

Array Designer designs thousands of primers and probes for oligo and cDNA microarrays in seconds. It designs probes for SNP detection, microarray gene expression and gene expression profiling. In addition, comprehensive support for tiling arrays and resequencing arrays is available.

::DEVELOPER

PREMIER Biosoft

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux / Windows

:: DOWNLOAD

Array Designer Demo

:: MORE INFORMATION

Mfuzz 2.31.0 – Soft Clustering of Microarray data

Mfuzz 2.31.0

:: DESCRIPTION

Mfuzz implementing soft clustering tools for microarray data analysis.

::DEVELOPER

Matthias E. Futschik

:: SCREENSHOTS

Mfuzz

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • R package
  • BioConductor
  • R-TclTk

:: DOWNLOAD

 Mfuzz

:: MORE INFORMATION

Citation

Mfuzz: a software package for soft clustering of microarray data.
Kumar L, E Futschik M.
Bioinformation. 2007 May 20;2(1):5-7.