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.

ArrayMining – Online Microarray Data Mining

ArrayMining

:: DESCRIPTION

ArrayMining is a server for automating statistical analysis of gene and protein expression microarray data, designed as a supporting tool for investigation of the genetic components of diseases.

::DEVELOPER

ArrayMining team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation:

BMC Bioinformatics. 2009 Oct 28;10:358. doi: 10.1186/1471-2105-10-358.
ArrayMining: a modular web-application for microarray analysis combining ensemble and consensus methods with cross-study normalization.
Glaab E, Garibaldi JM, Krasnogor N.

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.

VERA & SAM 1.0 – Find Significant Expression Differences in DNA Microarray Data

VERA & SAM 1.0

:: DESCRIPTION

VERA & SAM (Variability and ERror Assessment and Significance of Array Measurement) Estimates error model parameters from replicated, preprocessed experiments, and  uses error model to improve the accuracy of the expression ratio and to assign a value ‘lambda’ to each gene, indicating the likelihood that the gene is differentially expressed.

VERA and SAM are a pair of programs that provide a method to determine whether any given gene is expressed at a different level in one cell population than in another according to microarray data.

::DEVELOPER

the Ideker Lab

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux / Windows

:: DOWNLOAD

VERA & SAM

:: MORE INFORMATION

Citation

T. Ideker, V. Thorsson, A. F. Siegel, and L. Hood.
Testing for differentially-expressed genes by maximum-likelihood analysis of microarray data
Journal of Computational Biology 7 (6) 805-817 (2000).

Dapple 0.88pre4 – DNA Microarrays Image Analysis

Dapple 0.88pre4

:: DESCRIPTION

Dapple is a program for quantitating spots on a two-color DNA microarray image. Given a pair of images from a comparative hybridization, Dapple finds the individual spots on the image, evaluates their qualities, and quantifies their total fluorescent intensities.

Dapple is designed to work with microarrays on glass. The spot-finding techniques used are robust to uneven spot sizes and positional deviations caused by “wobbling” of the arraying robot, as well as image noise and artifacts. As long as your spots are consistently circular, Dapple has a good chance of finding them accurately.

::DEVELOPER

Jeremy Buhler

:: SCREENSHOTS

:: REQUIREMENTS

:: DOWNLOAD

Dapple

:: MORE INFORMATION

Citation:

J. Buhler, T. Ideker, D. Haynor, “Dapple: Improved Techniques for Finding Spots on DNA Microarrays”, University of Washington Department of Computer Science & Engineering Technical Report UW-CSE-2000-08-05, (2000)  Supplement.

GoSurfer 2.0 – Graphical Data Mining tool for Microarray data using Gene Ontology Information

GoSurfer 2.0

:: DESCRIPTION

GoSurfer uses Gene Ontology (GO) information to analyze gene sets obtained from genome-wide computations or microarray analyses. GoSurfer is a graphical interactive data mining tool. It associates user input genes with GO terms and visualizes such GO terms as a hierarchical tree. Users can manipulate the tree output by various means, like setting heuristic thresholds or using statistical tests. Significantly important GO terms resulted from a statistical test can be highlighted. All related information are exportable either as texts or as graphics.

::DEVELOPER

Zhong Lab

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows

:: DOWNLOAD

 GoSurfer

:: MORE INFORMATION

Citation

Zhong S, Storch F, Lipan O, Kao MJ, Weitz C, Wong WH.
GoSurfer: a graphical interactive tool for comparative analysis of large gene sets in Gene Ontology space.
Applied Bioinformatics 2004, 3(4): 1-5.

RPS 1.0 – Reproducibility Probability Score for Microarray Data

RPS 1.0

:: DESCRIPTION

RPS (Reproducibility Probability Score) computes reproducibility probability score  to select differentially expressed genes. The Reproducibility Probability Score (RPS), takes into consideration both the replicated data in a particular lab and the measurement variability across labs. The measurement variability is assessed by utilizing the reference gene expression data generated in the Microarray Quality Control (MAQC) project. Specifically, we applied the data generated across replicate gene expression analysis that was conducted in multiple facilities as part of this effort.  A larger RPS means a gene is more likely to be differentially expressed; and if similar transcription profiling measurements are made in other laboratories, it is highly likely to be confirmed.

::DEVELOPER

Zhong Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

  RPS

:: MORE INFORMATION

Citation

Guixian Lin, Xuming He, Hanlee Ji, Leming Shi, Ronald W. Davis, and Sheng Zhong.
Reproducibility Probability Score: Incorporating Measurement Variability across Laboratories for Gene Selection,
Nature Biotechnology 24, 1476 – 1477 (2006)

NACEP 20140602 – Network-based Comparison of Temporal Gene Expression Patterns

NACEP 20140602

:: DESCRIPTION

NACEP (Network-based comparison of temporal gene expression patterns) is a model-based, open source tool for time-course data analysis. It explicitly uses co-expression network information in comparison of temporal gene expression data.

::DEVELOPER

Zhong Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

  NACEP

:: MORE INFORMATION

Citation

Bioinformatics. 2010 Dec 1;26(23):2944-51. Epub 2010 Sep 30.
Network-based comparison of temporal gene expression patterns.
Huang W, Cao X, Zhong S.

PhylochipAnalyzer 1.0 – Analyse Hierarchical Probe sets

PhylochipAnalyzer 1.0

:: DESCRIPTION

PhylochipAnalyzer is a Windows-program for the analysis of experiments with hierarchical probe-sets. It operates in two modes: first, the hierarchy of probes is defined interactively, second, the intensity data of a hybridized chip is loaded and analyzed according to the hierarchy. The program can export hierarchy trees to Newick-format and analyzed data to Excel. It contains a Delphi-script that makes it configurable with respect to different criteria for positive signals.

::DEVELOPER

Bioinformatics at AWI

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows

:: DOWNLOAD

PhylochipAnalyzer

:: MORE INFORMATION

Citation:

Metfies K, Borsutzki P, Gescher C, Medlin LK, Frickenhaus S
Phylochipanalyser — a program for analysing hierarchical probe sets
Molecular Ecology Resources (2008) 8, 99–102
doi:10.1111/j.1471-8286.2007.01927.x

TACITuS 0.2.0 – Transcriptomic Data Collector, Integrator, and Selector

TACITuS 0.2.0

:: DESCRIPTION

TACITuS is a portal, which deals with data pre-processing, selection and, eventually, integration of transcriptomic data coming from diverse sources, such as ArrayExpress.

::DEVELOPER

Alfredo Pulvirenti

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

NO

:: MORE INFORMATION

Citation:

TACITuS: transcriptomic data collector, integrator, and selector on big data platform.
Alaimo S, Di Maria A, Shasha D, Ferro A, Pulvirenti A.
BMC Bioinformatics. 2019 Nov 22;20(Suppl 9):366. doi: 10.1186/s12859-019-2912-4.