RZ-smooth 3.5 – Resample, Smooth and Normalize Microarray time-series data

RZ-smooth 3.5

:: DESCRIPTION

RZ-smooth is a tool to resample (upsample), smooth and to normalize the input microarray data. The results can be compromised without the data pre-processing. RZ-smooth program takes as an input a matrix, where rows correspond to individual genes and columns correspond to different time points.

::DEVELOPER

Dmitri Papatsenko

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Windows

:: DOWNLOAD

RZ-smooth

:: MORE INFORMATION

Citation

Goltsev Y, Papatsenko D.
“Time warping of evolutionary distant temporal gene expression data based on noise suppression”
BMC Bioinformatics. 2009 Oct 26;10:353.

GSIM – Microarray Gene Expression Simulator

GSIM

:: DESCRIPTION

GSIM (Gene Expression Simulator) is a C program which simulates gene expression microarray data. It will generate distributions for any number of genes and use those distributions to generate intensities for any number of replicates. It generates two-class data and any number of the genes can be chosen to be differentially expressed. The program is very flexible and the parameters of the differentially expressed genes can be set by the user.

::DEVELOPER

the Computational Biology and Informatics Laboratory (in the Center for Bioinformatics at the University of Pennsylvania)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux/ MacOsX / Windows
Perl
C Compiler

:: DOWNLOAD

GSIM

:: MORE INFORMATION

ArrayOme 1.0 – Estimate the sizes of Microarray-visualised Bacterial Genomes

ArrayOme 1.0

:: DESCRIPTION

ArrayOme is a new software system to predict the size of the microarray-visualised genome (MVG) based on microarray-derived comparative genomic hybridization data.

::DEVELOPER

Hong-Yu Ou (tjohy@hotmail.com)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux / Windows

:: DOWNLOAD

ArrayOme

:: MORE INFORMATION

Citation:

Hong-Yu Ou et al.
ArrayOme: a program for estimating the sizes of microarray-visualized bacterial genomes
Nucl. Acids Res. (2005) 33 (1): e3.

FindProbe v2 – Design Probes for Microarrays

FindProbe v2

:: DESCRIPTION

FindProbe is a software for research involves designing probes for microarrays. Existing algorithms usually select probes using the criteria of homogeneity, sensitivity, and specificity. This project proposes to include one additional criterion, uniformity, which further improves the quality of the probes selected. It makes use of some smart filtering techniques to avoid redundant computation while maintaining accuracy.

::DEVELOPER

Dr. Sung Wing Kin, Ken

:: REQUIREMENTS

Linux/Windows/MacOsX
C Compiler

:: DOWNLOAD

FindProbe

:: MORE INFORMATION

Citation:

Proc IEEE Comput Soc Bioinform Conf. 2003;2:65-74.
Fast and accurate probe selection algorithm for large genomes.
Sung WK, Lee WH.

CHROMOWAVE 1.0 – Microarrays Data Analysis

CHROMOWAVE 1.0

:: DESCRIPTION

CHROMOWAVE is a toolbox written for Matlab 7. It performs pre-processing and analysis of microarray data. Although it was designed for Affymetrix microarrays, its use can be extended to other microarray data. Code is optimized in regards to memory use and speed. Pre-processing tools include array normalization and data matrix manipulations. Analysis tools include analysis of variance (paired, group and ANOVA analyses, correlation analysis, gene-classifiers) with relative multiple hypothesis testing corrections (FWER, FDR etc), analysis of co-variance (singular value decomposition. For Affymetrix data only, CHROMOWAVE can perform chromosomal analysis

::DEVELOPER

Dr Federico E Turkheimer

:: SCREENSHOTS

:: REQUIREMENTS

Linux / Windows/ MacOsX
Matlab

:: DOWNLOAD

CHROMOWAVE

:: MORE INFORMATION

Citation

Federico E Turkheimer et al.
Chromosomal patterns of gene expression from microarray data: methodology, validation and clinical relevance in gliomas
BMC Bioinformatics 2006, 7:526

ExpressYourself – Microarray Data Processing Platform

ExpressYourself

:: DESCRIPTION

ExpressYourself is an interactive platform for background correction, normalization, scoring, and quality assessment of raw microarray data.

::DEVELOPER

Gerstein Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux
web serve
Perl

:: DOWNLOAD

ExpressYourself

:: MORE INFORMATION

Citation:

NM Luscombe, TE Royce, P Bertone, N Echols, CE Horak, JT Chang, M Snyder, M Gerstein (2003).
ExpressYourself: A modular platform for processing and visualizing microarray data.
Nucleic Acids Res 31:3477-82.

MIMAS 3.0 – Microarray Information Management and Annotation System

MIMAS 3.0

:: DESCRIPTION

MIMAS (Microarray Information Management and Annotation System) is a freely available system for annotation of GeneChip and BeadArray experiments in a MIAME-compliant manner

::DEVELOPER

MIMAS team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux/Windows/MacOsX
perl
Web Server

:: DOWNLOAD

MIMAS

:: MORE INFORMATION

Citation

BMC Bioinformatics. 2009 May 18;10:151.
MIMAS 3.0 is a Multiomics Information Management and Annotation System.
Gattiker A, Hermida L, Liechti R, Xenarios I, Collin O, Rougemont J, Primig M.

EPIG – Extract Microarray Gene Expression Patterns and Identifying co-expressed Genes

EPIG

:: DESCRIPTION

EPIG (Extracting Patterns and Identifying co-expressed Genes) is a method for Extracting microarray gene expression Patterns and Identifying co-expressed Genes. Through evaluation of the correlations among profiles, the magnitude of variation in gene expression profiles, and profile signal-to-noise ratios, EPIG extracts a set of patterns representing co-expressed genes without a pre-defined seeding of the patterns.

::DEVELOPER

Clarice R. Weinberg, Ph.D.

:: SCREENSHOTS

:: REQUIREMENTS

Linux / Windows /MacOsX
Java

:: DOWNLOAD

EPIG

:: MORE INFORMATION

Citation:

BMC Bioinformatics. 2007 Nov 2;8:427.
Extracting gene expression patterns and identifying co-expressed genes from microarray data reveals biologically responsive processes.
Chou JW, Zhou T, Kaufmann WK, Paules RS, Bushel PR.

SVN – Remove Systematic Variation in Microarray Gene Expression data

SVN

:: DESCRIPTION

SVN (Systematic variation normalization) is a procedure for removing systematic variation in microarray gene expression data. Based on an analysis of how systematic variation contributes to variability in microarray data sets, the SVN procedure includes background subtraction determined from the distribution of pixel intensity values and log conversion, linear or non-linear regression, restoration or transformation, and multiarray normalization.

::DEVELOPER

Pierre R. Bushel, Ph.D.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux / Windows /MacOsX
Java

:: DOWNLOAD

SVN

:: MORE INFORMATION

Citation:

Chou JW, Paules RS, Bushel PR.
Systematic variation normalization in microarray data to get gene expression comparison unbiased.
J Bioinform Comput Biol. 2005 Apr;3(2):225-41.

SignalViewer – Image Analysis of cDNA Microarrays

SignalViewer

:: DESCRIPTION

SignalViewer is a Software Application for Image Analysis of cDNA Microarrays

::DEVELOPER

Fred Hutchinson Cancer Research Center

:: SCREENSHOTS

:: REQUIREMENTS

Windows / Linux

:: DOWNLOAD

SignalViewer

:: MORE INFORMATION

Citation

Laws RJ, Bergemann TL, Quiaoit F, Zhao LP.
SignalViewer: analyzing microarray images.
Bioinformatics. 2003 Sep 1;19(13):1716-7.