GENS 2.3.1 – Simulate Gene-environment and Gene-gene Interactions

GENS 2.3.1

:: DESCRIPTION

GENS2 (Gene-Environment iNteraction Simulator) simulates interactions among two genetic and one environmental factor and also allows for epistatic interactions. GENS2 is based on data with realistic patterns of linkage disequilibrium, and imposes no limitations either on the number of individuals to be simulated or on number of non-predisposing genetic/environmental factors to be considered.

::DEVELOPER

Gruppo Interdipartimentale di Bioinformatica e Biologia Computazionale, Università di Napoli “Federico II”

:: SCREENSHOTS

GENS

::REQUIREMENTS

  • Linux/ MacOsX/Windows
  • Python

:: DOWNLOAD

  GENS

:: MORE INFORMATION

Citation

Simulating gene-gene and gene-environment interactions in complex diseases: Gene-Environment iNteraction Simulator 2.
Pinelli M, Scala G, Amato R, Cocozza S, Miele G.
BMC Bioinformatics. 2012 Jun 14;13:132. doi: 10.1186/1471-2105-13-132.

epistasisGA – Detecting Gene-gene Interactions in Case-parent Triad or Affected/unaffected Sibling studies

epistasisGA

:: DESCRIPTION

The epistasisGA package implements the GADGETS approach for detecting gene-gene interactions in case-parent triad or affected/unaffected sibling studies.

GADGETS is genetic algorithm for detecting epistasis using nuclear families

::DEVELOPER

Michael Nodzenski

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / MacOsX
  • R

:: DOWNLOAD

epistasisGA

:: MORE INFORMATION

Citation:

Nodzenski M, Shi M, Krahn JM, Wise AS, Li Y, Li L, Umbach DM, Weinberg CR.
GADGETS: A genetic algorithm for detecting epistasis using nuclear families.
Bioinformatics. 2021 Nov 12:btab766. doi: 10.1093/bioinformatics/btab766. Epub ahead of print. PMID: 34788792.

GEsnpx 1.1 / GEsnpxPara 1.3 – Genetic Ensemble approach for Gene-gene Interaction Identification

GEsnpx 1.1 / GEsnpxPara 1.3

:: DESCRIPTION

GEsnpx is a Java implementation of genetic ensemble algorithm for gene-gene interaction identification

GEsnpxPara is a parallel version of genetic ensemble algorithm

::DEVELOPER

GEsnpx team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux /  Windows / MacOsX
  • Java
:: DOWNLOAD

 GEsnpx / GEsnpxPara

:: MORE INFORMATION

Citation

BMC Bioinformatics. 2010 Oct 21;11:524. doi: 10.1186/1471-2105-11-524.
A genetic ensemble approach for gene-gene interaction identification.
Yang P1, Ho JW, Zomaya AY, Zhou BB.

TuRF-E 1.0 – Gene-gene Interaction Giltering with Ensemble of Filters

TuRF-E 1.0

:: DESCRIPTION

Providing TuRF-E program for SNP interaction filtering.

::DEVELOPER

TuRF-E team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux /  Windows / MacOsX
  • Perl
:: DOWNLOAD

 TuRF-E

:: MORE INFORMATION

Citation

BMC Bioinformatics. 2011 Feb 15;12 Suppl 1:S10. doi: 10.1186/1471-2105-12-S1-S10.
Gene-gene interaction filtering with ensemble of filters.
Yang P1, Ho JW, Yang YH, Zhou BB.

SPA3G 1.0 – Gene-centric Gene-Gene Interaction

SPA3G 1.0

:: DESCRIPTION

SPA3G implements the model-based kernel machine method for detecting gene-centric gene-gene interactions.

::DEVELOPER

Yuehua Cui, Ph.D.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux
  • R

:: DOWNLOAD

 SPA3G

:: MORE INFORMATION

Citation:

Li SY and YH Cui. (2012)
Gene-centric gene-gene interaction: a model-based kernel machine method.
Annals of Applied Statistics 6(3): 1134-1161.

GeneNetVal – Gene Network Biological Validity based on Gene-gene Interaction Relevance

GeneNetVal

:: DESCRIPTION

GeneNetVal is a Java application for network analysis. The application uses the metabolic pathways stored in kegg to rate the validity of an input network.

::DEVELOPER

GeneNetVal team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/ Windows
  • Java

:: DOWNLOAD

 GeneNetVal

:: MORE INFORMATION

Citation:

ScientificWorldJournal. 2014;2014:540679. doi: 10.1155/2014/540679. Epub 2014 Sep 8.
Gene network biological validity based on gene-gene interaction relevance.
Gómez-Vela F, Díaz-Díaz N.

BOOST 20101230 / GBOOST 20130821 – Detect Gene-gene Interactions

BOOST 20101230 / GBOOST 20130821

:: DESCRIPTION

BOOST (BOolean Operation based Screening and Testing) is a method for detecting gene-gene interactions. It allows examining all pairwise interactions in genome-wide case-control studies in a remarkably fast manner. Interaction analyses on seven data sets from the Wellcome Trust Case Control Consortium were carried out.

GBOOST is a GPU-implementation of BOOST based on the CUDA technology by Nvidia.

::DEVELOPER

Laboratory for Bioinformatics and Computational Biology, HKUST

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 BOOST , GBOOST

:: MORE INFORMATION

Citation:

Wan, Yang, Yang, Xue, Fan, Tang, Yu (2010),
BOOST: a Boolean representation-based method for detecting SNP-SNP interactions in genome-wide association studies“”,
American Journal of Human Genetics, 87:325-340.

L. S. Yung, C. Yang, X. Wan, and W. Yu
GBOOST : A GPU-based tool for detecting gene-gene interactions in genome-wide case control studies“,
Bioinformatics, 27:1309-1310, 2011.

NetGSRforGGInt – Detection of Gene-Gene Interactions

NetGSRforGGInt

:: DESCRIPTION

NetGSRforGGInt is the algorithm that implemented the network-guided sparse regression for interaction detection

::DEVELOPER

Eric D. Kolaczyk

:: SCREENSHOTS

n/A

:: REQUIREMENTS

  • Linux / Windows/ MacOsX
  • R package

:: DOWNLOAD

 NetGSRforGGInt

:: MORE INFORMATION

Citation

Lu, C., Latourelle, J., O’Connor, G.T., Dupuis, J., and Kolaczyk, E.D. (2013).
Network-guided sparse regression modeling for detection of gene-by-gene interactions.
Bioinformatics, 29(10), 1241-1249.

GCORE 201510 – Fast Family-based Gene-gene Interaction Test

GCORE 201510

:: DESCRIPTION

GCORE is an efficient family-based gene-gene interaction test for trios.

::DEVELOPER

Statistical Genetics and Programming Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 GSCORE

:: MORE INFORMATION

Citation

An efficient gene-gene interaction test for genome-wide association studies in trio families.
Sung PY, Wang YT, Yu YW, Chung RH.
Bioinformatics. 2016 Feb 11. pii: btw077.

HapEvolution – Detect Gene-gene Interactions from Case-control Haplotype data

HapEvolution

:: DESCRIPTION

HapEvolution is a cooperative coevolutionary algorithm (CCA) to detect gene-gene interactions from case-control haplotype data; moreover, this algorithm can tolerate up to 15% missing/ambiguous positions in haplotype data arising during haplotype phasing from genotypes. Further, the algorithm can compute epistatic associations from genes spanning multiple chromosomes.

::DEVELOPER

Population Therapeutics Research Group

:: SCREENSHOTS

HapEvolution

:: REQUIREMENTS

  • Linux / MacOsX / Windows
  • Java

:: DOWNLOAD

  HapEvolution

:: MORE INFORMATION