spkTools 1.43.0 – Collection of Functions to Analyze Microarray Spike-in data

spkTools 1.43.0

:: DESCRIPTION

spkTools contains functions that can be used to compare expression measures on different array platforms.

::DEVELOPER

Matthew N. McCall

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / MacOsX / Linux
  • R package
  • Bioconductor

:: DOWNLOAD

 spkTools

:: MORE INFORMATION

Citation

Nucleic Acids Res. 2008 Oct;36(17):e108. doi: 10.1093/nar/gkn430. Epub 2008 Aug 1.
Consolidated strategy for the analysis of microarray spike-in data.
McCall MN, Irizarry RA.

SAM 4.01 – Significance Analysis of Microarrays

SAM 4.01

:: DESCRIPTION

SAM (Significance Analysis of Microarrays) is a statistical technique for finding significant genes in a set of microarray experiments, a supervised learning software for genomic expression data mining.

The input to SAM is gene expression measurements from a set of microarray experiments, as well as a response variable from each experiment. The response variable may be a grouping like untreated, treated [either unpaired or paired], a multiclass grouping (like breast cancer, lymphoma, colon cancer, . . . ), a quantitative variable (like blood pressure) or a possibly censored survival time.

::DEVELOPER

Stanford University Statistics and Biochemistry Labs

:: SCREENSHOTS

:: REQUIREMENTS

:: DOWNLOAD

 SAM

:: MORE INFORMATION

Citation

Jun Li and Robert Tibshirani (2011)
Finding consistent patterns: a nonparametric approach for identifying differential expression in RNA-Seq data.
Stat Methods Med Res. 2011 Nov 28.

RobiNA 1.2.4 – Open Source Microarray and RNA-Seq Processing

RobiNA 1.2.4

:: DESCRIPTION

RobiNA is an integrated solution that consolidates all steps of RNA-Seq-based differential gene-expression analysis in one user-friendly cross-platform application featuring a rich graphical user interface. RobiNA accepts raw FastQ files, SAM/BAM alignment files and counts tables as input. It supports quality checking, flexible filtering and statistical analysis of differential gene expression based on state-of-the art biostatistical methods developed in the R/Bioconductor projects. In-line help and a step-by-step manual guide users through the analysis.

::DEVELOPER

Max Planck Institute for Molecular Plant Physiology

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows/Linux/MacOsX
  • Java

:: DOWNLOAD

 RobiNA

:: MORE INFORMATION

Citation

Lohse M, Bolger AM, Nagel A, Fernie AR, Lunn JE, Stitt M, Usadel B. (2012)
RobiNA: A user-friendly, integrated software solution for RNA-Seq-based transcriptomics.
Nucleic Acids Res. 2012 Jul;40(Web Server issue):W622-7.

AIM 0.82 – Automatic Image Processing for Microarrays

AIM 0.82

:: DESCRIPTION

AIM (Automatic Image Processing for Microarrays) is designed for uncalibrated microarray gridding and quantitative image analysis.Uncalibrated microarray image analysis supports integration of expression data from different sources and can improve reproducibility.

::DEVELOPER

Mathias Katzer

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

AIM

:: MORE INFORMATION

Citation

M. Katzer and and F. Kummert and G. Sagerer:
Methods for Automatic Microarray Image Segmentation.
IEEE Transactions on Nano-Bioscience, 2003, pages 202-214

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.