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.

PAA 1.4.1 – Biomarker Discovery with Protein Microarrays

PAA 1.4.1

:: DESCRIPTION

The R/Bioconductor package PAA (Protein Array Analyzer) facilitates a flexible analysis of protein microarrays for biomarker discovery (esp., ProtoArrays).

::DEVELOPER

Medizinisches Proteom-Center

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux / Mac OsX
  • R/ BioConductor

:: DOWNLOAD

 PAA

:: MORE INFORMATION

Citation

PAA: An R/Bioconductor package for biomarker discovery with protein microarrays.
Turewicz M, Ahrens M, May C, Marcus K, Eisenacher M.
Bioinformatics. 2016 Jan 22. pii: btw037

Chipster 3.7 – Analysis software for Microarray and other High-throughput data

Chipster 3.7

:: DESCRIPTION

Chipster is a user-friendly analysis software for high-throughput data. It contains over 280 analysis tools for next generation sequencing (NGS), microarray and proteomics data.

::DEVELOPER

CSC — IT Center for Science Ltd

:: SCREENSHOTS

Chipster

:: REQUIREMENTS

  • Linux / Windows /MacOsX
  • Java

:: DOWNLOAD

  Chipster

:: MORE INFORMATION

Citation

BMC Genomics. 2011 Oct 14;12:507. doi: 10.1186/1471-2164-12-507.
Chipster: user-friendly analysis software for microarray and other high-throughput data.
Kallio MA, Tuimala JT, Hupponen T, Klemelä P, Gentile M, Scheinin I, Koski M, Käki J, Korpelainen EI.

GuidedClustering 0.9 – Combined analysis of a Microarray and Experimental data

GuidedClustering 0.9

:: DESCRIPTION

GuidedClustering is an R package for the joint analysis of clinical microarray profiles and additional per gene measurements.

::DEVELOPER

Institute of Functional Genomics

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux / MacOsX
  • R

:: DOWNLOAD

 GuidedClustering

:: MORE INFORMATION

Citation

Bioinformatics. 2011 Aug 15;27(16):2231-8. doi: 10.1093/bioinformatics/btr363. Epub 2011 Jun 17.
Genomic data integration using guided clustering.
Maneck M1, Schrader A, Kube D, Spang R.

Re-Annotator 1.0.0 – Re-annotates Microarray Probes

Re-Annotator 1.0.0

:: DESCRIPTION

Re-Annotator is a re-annotation pipeline for gene expression microarrays that will bring probe annotations up-to-date!

::DEVELOPER

André Altmann

:: SCREENSHOTS

n/a

:: REQUIREMENTS

  • Linux
  • Perl, BWA,SAMtools,Annovar

:: DOWNLOAD

  Re-Annotator

:: MORE INFORMATION

Citation

Re-Annotator: Annotation Pipeline for Microarray Probe Sequences.
Arloth J, Bader DM, Röh S, Altmann A.
PLoS One. 2015 Oct 1;10(10):e0139516. doi: 10.1371/journal.pone.0139516

KegArray 1.2.4 – Microarray Data Analysis & Cluster

KegArray 1.2.4

:: DESCRIPTION

KegArray is a Java application that provides an environment for analyzing both transcriptome data (gene expression profiles) and metabolome data (compound profiles). Tightly integrated with the KEGG database, KegArray enables you to easily map those data to KEGG resources including PATHWAY, BRITE and genome maps.

::DEVELOPER

Kanehisa Laboratories

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows / Mac /  Linux
  • Java

:: DOWNLOAD

KegArray

:: MORE INFORMATION

Citation

Methods Mol Biol. 2012;802:19-39.
The KEGG databases and tools facilitating omics analysis: latest developments involving human diseases and pharmaceuticals.
Kotera M, Hirakawa M, Tokimatsu T, Goto S, Kanehisa M.

OOMPA 3.1.0 – Object-Oriented Microarray and Proteomic Analysis

OOMPA 3.1.0

:: DESCRIPTION

OOMPA is an object-oriented microarray and proteomics analysis library implemented in R using S4 classes and compatible with BioConductor.

OOMPA includes experimental versions of two new packages:

  • ArrayCube: builds on fundamental classes from BioConductor to define a structure that generalizes the MINiML format used at the Gene Expression Omnibus. The main enhancement over MINiML format is the inclusion of an annotated data frame containing sample characteristics. The package provides routines to convert an ArrayCube into either an AffyBatch or an RGList, as appropriate.
  • MINiML: reads files in the MINiML format, as downloaded from the Gene Expression Omnibus, and stores them in R as ArrayCubes.

::DEVELOPER

Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 OOMPA

:: MORE INFORMATION

Citation

Development of a robust classifier for quality control of reverse-phase protein arrays.
Ju Z, Liu W, Roebuck PL, Siwak DR, Zhang N, Lu Y, Davies MA, Akbani R, Weinstein JN, Mills GB, Coombes KR.
Bioinformatics. 2014 Nov 6. pii: btu736.

SIBER: systematic identification of bimodally expressed genes using RNAseq data.
Tong P, Chen Y, Su X, Coombes KR.
Bioinformatics. 2013 Mar 1;29(5):605-13. doi: 10.1093/bioinformatics/bts713. Epub 2013 Jan 9

integIRTy: a method to identify genes altered in cancer by accounting for multiple mechanisms of regulation using item response theory.
Tong P, Coombes KR.
Bioinformatics. 2012 Nov 15;28(22):2861-9. doi: 10.1093/bioinformatics/bts561

Cancer Inform. 2009 Aug 5;7:199-216.
The bimodality index: a criterion for discovering and ranking bimodal signatures from cancer gene expression profiling data.
Wang J, Wen S, Symmans WF, Pusztai L, Coombes KR.