rapmad – Robust Analysis of Peptide MicroArray Data

rapmad

:: DESCRIPTION

rapmad is an R-package for the Robust Analysis of Peptide MicroArray Data. It is an automated, multi-step approach that combines several computational and statistical procedures to improve the quality of peptide microarray data and thus enable a more reliable analysis.

::DEVELOPER

The Institute for Translational Oncology and Immunology (TrOn)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux /MacOsX
  • R package

:: DOWNLOAD

   rapmad

:: MORE INFORMATION

Citation

BMC Bioinformatics. 2011 Aug 4;12:324. doi: 10.1186/1471-2105-12-324.
rapmad: Robust analysis of peptide microarray data.
Renard BY, Löwer M, Kühne Y, Reimer U, Rothermel A, Türeci O, Castle JC, Sahin U.

GemiNI – Network based integration of Gene Expression profiles with miRNA Expression Profiles

GemiNI

:: DESCRIPTION

GemiNI /dChip-GemiNi (Gene and miRNA Network-based Integration) is a web server which is an integrative analysis of gene and miRNA expression profiles with transcription factor-miRNA feed-forward loops

::DEVELOPER

Cheng Li Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 GemiNI

:: MORE INFORMATION

Citation

Nucleic Acids Res. 2012 Sep 1;40(17):e135.
Integrative analysis of gene and miRNA expression profiles with transcription factor-miRNA feed-forward loops identifies regulators in human cancers.
Yan Z, Shah PK, Amin SB, Samur MK, Huang N, Wang X, Misra V, Ji H, Gabuzda D, Li C.

SLIM 1.1 – Sliding Linear Model for Estimating the Proportion of true null Hypotheses in Datasets

SLIM 1.1

:: DESCRIPTION

SLIM (Sliding Linear Model) is a software to more reliably estimate π(0) under dependence. When tested on a number of simulation datasets with varying data dependence structures and on microarray data, SLIM was found to be robust in estimating π(0) against dependence. The accuracy of its π(0) estimation suggests that SLIM can be used as a stand-alone tool for prediction of significant tests.

::DEVELOPER

 the Tsai lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows / MacOsX
:: DOWNLOAD

 SLIM

:: MORE INFORMATION

Citation

Bioinformatics. 2011 Jan 15;27(2):225-31. Epub 2010 Nov 18.
SLIM: a sliding linear model for estimating the proportion of true null hypotheses in datasets with dependence structures.
Wang HQ, Tuominen LK, Tsai CJ.

FARMS 1.38.0 – Factor Analysis for Robust Microarray Summarization

FARMS 1.38.0

:: DESCRIPTION

FARMS (Factor Analysis for Robust Microarray Summarization ) is a model-based technique for summarizing high-density oligonucleotide array data at probe level for Affymetrix GeneChips. It is based on a factor analysis model for which a Bayesian maximum a posteriori method optimizes the model parameters under the assumption of Gaussian measurement noise. The comparison on the Affymetrix spiked-in bechmark data shows the excellent sensitivity and specificity performance of FARMS.

::DEVELOPER

Institute of Bioinformatics, Johannes Kepler University Linz

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 FARMS

:: MORE INFORMATION

Citation

Sepp Hochreiter, Djork-Arné Clevert, and Klaus Obermayer.
A new summarization method for affymetrix probe level data.”
Bioinformatics 2006 22(8):943-949;

cn.FARMS 1.34.0 – Factor Analysis for Copy Number Estimation

cn.FARMS 1.34.0

:: DESCRIPTION

cn.FARMS is a latent variable model for detecting copy number variations in microarray data.

::DEVELOPER

Institute of Bioinformatics, Johannes Kepler University Linz

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux / Mac OsX
  • R Package
  • BioConductor

:: DOWNLOAD

 cn.FARMS

:: MORE INFORMATION

Citation

Nucleic Acids Res. 2011 Jul;39(12):e79. doi: 10.1093/nar/gkr197. Epub 2011 Apr 12.
cn.FARMS: a latent variable model to detect copy number variations in microarray data with a low false discovery rate.
Clevert DA1, Mitterecker A, Mayr A, Klambauer G, Tuefferd M, De Bondt A, Talloen W, G?hlmann H, Hochreiter S.

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.

BicOverlapper 2.0 – Visual Analysis of Gene Expression

BicOverlapper 2.0

:: DESCRIPTION

BicOverlapper is a framework to support visual analysis of gene expression by means of biclustering.

BicOverlapper is a tool to visualize biclusters from gene-expression matrices in a way that helps to compare biclustering methods, to unravel trends and to highlight relevant genes and conditions. A visual approach can complement biological and statistical analysis and reduce the time spent by specialists interpreting the results of biclustering algorithms. The technique is based on a force-directed graph where biclusters are represented as flexible overlapped groups of genes and conditions.

::DEVELOPER

The VisUsal (Visual Analytics and Information Visualization, Universidad de Salamanca) group

:: SCREENSHOTS

:: REQUIREMENTS

:: DOWNLOAD

BicOverlapper

:: MORE INFORMATION

Citation

BicOverlapper 2.0: visual analysis for gene expression.
Santamaría R, Therón R, Quintales L.
Bioinformatics. 2014 Jun 15;30(12):1785-6. doi: 10.1093/bioinformatics/btu120

Santamaría, R.; Therón, R. & Quintales, L.
BicOverlapper: A tool for bicluster visualization.
Bioinformatics, 2008, 24, 1212-1213

PIIKA 2 – Analyzing data originating from Kinome Microarrays

PIIKA 2

:: DESCRIPTION

PIIKA (Platform for Intelligent, Integrated Kinome Analysis) is a tool for analyzing data originating from kinome microarrays.

::DEVELOPER

Bioinformatics Research Group, University of Saskatchewan

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

PLoS One. 2013 Nov 29;8(11):e80837. doi: 10.1371/journal.pone.0080837. eCollection 2013.
PIIKA 2: an expanded, web-based platform for analysis of kinome microarray data.
Trost B1, Kindrachuk J, Määttänen P, Napper S, Kusalik A.

Probe Select – Select Oligos for DNA Microarray

Probe Select

:: DESCRIPTION

Probe Select is the probes program to select oligos for DNA microarray.

::DEVELOPER

Stormo Lab in Department of Genetics, Washington University

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

  Probe Select

:: MORE INFORMATION

Citation

Bioinformatics. 2001 Nov;17(11):1067-76.
Selection of optimal DNA oligos for gene expression arrays.
Li F, Stormo GD.
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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)