GEOmetadb 1.52.0 – GEO Microarray Search Tool

GEOmetadb 1.52.0

:: DESCRIPTION

GEOmetadb is an attempt to make access to the metadata associated with the NCBI Gene Expression Omnibus (GEO) samples, platforms, and datasets much more feasible for common biologists and bioinformatians/statistians.

::DEVELOPER

Jack Zhu , Sean Davis @NCI

:: SCREENSHOTS

N/A

::REQUIREMENTS

  • Linux/ Windows/ MacOsX
  • R package
  • BioConductor

:: DOWNLOAD

 GEOmetadb

:: MORE INFORMATION

Citation

Bioinformatics. 2008 Dec 1;24(23):2798-800. doi: 10.1093/bioinformatics/btn520.
GEOmetadb: powerful alternative search engine for the Gene Expression Omnibus.
Zhu Y, Davis S, Stephens R, Meltzer PS, Chen Y.

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

OLIN 1.68.0 – Optimized Normalization, Visualization and Quality Testing of two-channel Microarray data

OLIN 1.68.0

:: DESCRIPTION

OLIN (Optimised Local Intensity-dependent Normalisation) is the software developed for optimized normalization.

::DEVELOPER

SysBioLab

:: SCREENSHOTS

:: REQUIREMENTS

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

:: DOWNLOAD

 OLIN

:: MORE INFORMATION

Citation

Bioinformatics. 2005 Apr 15;21(8):1724-6.
OLIN: optimized normalization, visualization and quality testing of two-channel microarray data.
Futschik ME, Crompton T.

Mfuzz 2.51.0 – Soft Clustering of Microarray data

Mfuzz 2.51.0

:: DESCRIPTION

Mfuzz implementing soft clustering tools for microarray data analysis.

::DEVELOPER

SysBioLab

:: SCREENSHOTS

:: 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.

dChip 2011.12 – Analysis & Visualization of Gene Expression & SNP Microarrays

dChip 2011.12

:: DESCRIPTION

DNA-Chip Analyzer (dChip) is a Windows software package for probe-level (e.g. Affymetrix platform) and high-level analysis of gene expression microarrays and SNP microarrays.

Gene expression or SNP data from various microarray platforms can also be analyzed by importing as external dataset. At the probe level, dChip can display and normalize the CEL files, and the model-based approach allows pooling information across multiple arrays and automatic probe selection to handle cross-hybridization and image contamination. High-level analysis in dChip includes comparing samples, hierarchical clustering, view expression and SNP data along chromosome, LOH and copy number analysis of SNP arrays, and linkage analysis. In these functions the gene information and sample information are correlated with the analysis results.

::DEVELOPER

Started in Wing Wong Lab , Developed & Maintained by Cheng Li Lab.

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows
  • Linux with Wine
  • Mac with Virtual PC

:: DOWNLOAD

dChip

:: MORE INFORMATION

Please cite Li and Wong 2001a if dChip results are used in manuscripts, and cite Lin et al. 2004 if dChip SNP analysis functions are used.

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

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