PTest 20130115 – Testing set of observed small P-values in GWAS

PTest 20130115

:: DESCRIPTION

PTest (Partition test) is a software for case-control genetic association studies in human gene mapping. The PTest is based on single-SNP p-values resulting from an association test, for example, the chi-square test comparing genotype or allele frequencies in cases and controls.

::DEVELOPER

Jurg Ott, Ph.D.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux

:: DOWNLOAD

 PTest

:: MORE INFORMATION

Citation

Challenging false discovery rate: a partition test based on p values in human case-control association studies.
Ott J, Liu Z, Shen Y.
Hum Hered. 2012;74(1):45-50. doi: 10.1159/000343752. Epub 2012 Nov 13.

THESIAS 3.1.1 – Testing Haplotype Effects In Association Studies

THESIAS 3.1.1

:: DESCRIPTION

The objectif of the THESIAS program is to performed haplotype-based association analysis in unrelated individuals. This program is based on the maximum likelihood model.THESIAS allows one to simultaneous estimate haplotype frequencies and their associated effects on the phenotype of interest. In this new THESIAS release, quantitative, qualitative (logistic and matched-pair analysis), categorical and survival outcomes can be studied. X-linked haplotype analysis is also feasible.

::DEVELOPER

Tregouet David <tregouet@chups.jussieu.fr>
Garelle Valérie (garelle@chups.jussieu.fr)

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows/Linux
  • Java

:: DOWNLOAD

  THESIAS

:: MORE INFORMATION

Citation

Tregouet DA, Garelle V.
A new JAVA interface implementation of THESIAS: Testing Haplotypes EffectS In Association Studies.
Bioinformatics. 2007;23(8):1038-1039.

miRtest 1.8 – Combined miRNA- and mRNA-testing

miRtest 1.8

:: DESCRIPTION

Expression levels of mRNAs are among other factors regulated by microRNAs. A particular microRNA can bind specifically to several target mRNAs and lead to their degradation. Expression levels of both, mRNAs and microRNAs, can be obtained by microarray experiments. In order to increase the power of detecting microRNAs that are differentially expressed between two different groups of samples, “miRtest” incorporates expression levels of their related target gene sets.

::DEVELOPER

miRtest team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux/MacOsX
  • R

:: DOWNLOAD

 miRtest

:: MORE INFORMATION

Citation

PLoS One. 2012;7(6):e38365. doi: 10.1371/journal.pone.0038365. Epub 2012 Jun 19.
Detection of simultaneous group effects in microRNA expression and related target gene sets.
Artmann S1, Jung K, Bleckmann A, Beissbarth T.

Broad-Enrich 2.14.0 – Gene Set Enrichment Testing for Sets of Broad Genomic Regions

Broad-Enrich 2.14.0

:: DESCRIPTION

Broad-Enrich tests sets of broad genomic regions (e.g., from ChIP-seq data for histone modifications or copy number variations) for enriched biological pathways, Gene Ontology terms, or other gene sets.

::DEVELOPER

The Sartor Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/Windows / MacOsX
  • R

:: DOWNLOAD

 Broad-Enrich

:: MORE INFORMATION

Citation

Broad-Enrich: functional interpretation of large sets of broad genomic regions.
Cavalcante RG, Lee C, Welch RP, Patil S, Weymouth T, Scott LJ, Sartor MA.
Bioinformatics. 2014 Sep 1;30(17):i393-i400. doi: 10.1093/bioinformatics/btu444.

Tarsier – Testing and Analysing RNA gene Software, Including Evolutionary Relationships

Tarsier

:: DESCRIPTION

Tarsier is a software pipeline for testing RNA gene prediction programs with genomic alignments. It automatically gathers RNA data from Rfam and genomic alignments from both UCSC and Ensembl, and executes two popular prediction programs, EvoFold and RNAz.

::DEVELOPER

Whelan Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows / MacOsX

:: DOWNLOAD

 contact with the author

:: MORE INFORMATION

Phylemon 2.0 – Web-tools for Molecular Evolution, Phylogenetics, Phylogenomics and Hypothesis testing

Phylemon 2.0

:: DESCRIPTION

Phylemon is the suite of web-tools for molecular evolution, phylogenetics and phylogenomics. It is conceived as a natural response to the increasing demand of data analysis of experimental scientists seeking to add molecular evolution and phylogenetic insight into their research.

::DEVELOPER

Bioinformatics and Genomics Department at CIPF

:: SCREENSHOTS

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 No, Only Web Service

:: MORE INFORMATION

Citation

Sánchez R, Serra F, Tárraga J, Medina I, Carbonell J, Pulido L, de María A, Capella-Gutíerrez S, Huerta-Cepas J, Gabaldón T, Dopazo J, Dopazo H.
Phylemon 2.0: a suite of web-tools for molecular evolution, phylogenetics, phylogenomics and hypotheses testing.
Nucleic Acids Res. 2011 Jul;39(Web Server issue):W470-4. Epub 2011 Jun 6.

IBMT – Testing for Differentially Expressed Genes in Microarrays

IBMT

:: DESCRIPTION

IBMT is a Bayesian hierarchical normal model to define a novel Intensity-Based Moderated T-statistic.The method is completely data-dependent using empirical Bayes philosophy to estimate hyperparameters, and thus does not require specification of any free parameters. IBMT has the strength of balancing two important factors in the analysis of microarray data: the degree of independence of variances relative to the degree of identity (i.e. t-tests vs. equal variance assumption), and the relationship between variance and signal intensity. When this variance-intensity relationship is weak or does not exist, IBMT reduces to a previously described moderated t-statistic. Furthermore, our method may be directly applied to any array platform and experimental design. Together, these properties show IBMT to be a valuable option in the analysis of virtually any microarray experiment.

:: DEVELOPER

Laboratory for Statistical Genomics, Univ. Cincinnati

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/MacOsX/Windows
  • R Package

:: DOWNLOAD

 IBMT

:: MORE INFORMATION

Citation:

BMC Bioinformatics. 2006 Dec 19;7:538.
Intensity-based hierarchical Bayes method improves testing for differentially expressed genes in microarray experiments.
Sartor MA, Tomlinson CR, Wesselkamper SC, Sivaganesan S, Leikauf GD, Medvedovic M.

STAC 1.2 – Significance Testing for Aberrant Copy-Number

STAC 1.2

:: DESCRIPTION

STAC (Significance Testing for Aberrant Copy-Number) is a method for testing the significance of DNA copy number aberrations across multiple array-CGH experiments. It utilizes two complementary statistics in combination with a novel search strategy. The significance of both statistics is assessed, and P-values are assigned to each location on the genome by using a multiple testing corrected permutation approach. STAC identifies genomic alterations known to be of clinical and biological significance and provides statistical support for 85% of previously reported regions. Moreover, STAC identifies numerous additional regions of significant gain/loss in these data that warrant further investigation. The P-values provided by STAC can be used to prioritize regions for follow-up study in an unbiased fashion.

::DEVELOPER

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

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux/ MacOsX / Windows
  •  Java

:: DOWNLOAD

 STAC

:: MORE INFORMATION

Citation:

Diskin SJ, Eck T, Greshock J, Mosse YP, Naylor T, Stoeckert CJ Jr, Weber BL, Maris JM, Grant GR.
STAC: A method for testing the significance of DNA copy number aberrations across multiple array-CGH experiments
Genome Res. 2006 Sep;16(9):1149-58. Epub 2006 Aug 9.

TRANSMIT 2.5.4 – Transmission Disequilibrium Testing

TRANSMIT 2.5.4

:: DESCRIPTION

TRANSMIT tests for association between genetic marker and disease by examining the transmission of markers from parents to affected offspring.

::DEVELOPER

David Clayton

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows with cygwin
  • C Compiler

:: DOWNLOAD

 TRANSMIT

:: MORE INFORMATION