TINGe 1.062 / GeNA 0.1 – Gene Networks Inference and Analysis

TINGe 1.062 / GeNA 0.1

:: DESCRIPTION

TINGe (Tool for Inferring Networks of GEnes) is a parallel and multi-platform framework for reconstructing gene regulatory networks from large gene expression data. It uses parallel processing, information theoretic criteria and statistical testing to derive networks with thousands of genes from microarray sets with thousands of observations. TINGe has been used to reconstruct a whole-genome network of Arabidopsis thaliana from 3,546 microarray measurements, which comprises of 15,495 genes.

GeNA (GEne Networks Analyzer) is a tool that for a given set of “seed” genes uses gene ranking mechanism to extract subnetworks of genes with similar biological function. GeNA uses algorithm akin to the topic-sensitive PageRank and it has been implemented as a stand-alone tool and as a plugin for Cytoscape.

::DEVELOPER

Prof. Srinivas Aluru Research group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 TINGe / GeNA 

:: MORE INFORMATION

Citation:

Jaroslaw Zola, et al.
Parallel Information-Theory-Based Construction of Genome-Wide Gene Regulatory Networks
IEEE Transactions on Parallel and Distributed Systems. December 2010 (vol. 21 no. 12) pp. 1721-1733

jump3 – Inference of Gene Regulatory Networks

jump3

:: DESCRIPTION

Jump3 is based on a formal on/off model of gene expression, but uses a non-parametric procedure based on decision trees (called “jump trees”) to reconstruct the GRN topology, allowing the inference of networks of hundreds of genes.

::DEVELOPER

vân anh huynh-thu

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • MatLab / R Package

:: DOWNLOAD

 jump3

:: MORE INFORMATION

Citation

Combining tree-based and dynamical systems for the inference of gene regulatory networks.
Huynh-Thu VA, Sanguinetti G.
Bioinformatics. 2015 Jan 7. pii: btu863.

GENIE3 – Inference of Gene Regulatory Networks from Expression data

GENIE3

:: DESCRIPTION

GENIE3 is an algorithm for the inference of gene regulatory networks from expression data. It decomposes the prediction of a regulatory network between p genes into p different regression problems. In each of the regression problems, the expression pattern of one of the genes (target gene) is predicted from the expression patterns of all the other genes (input genes), using tree-based ensemble methods Random Forests or Extra-Trees. The importance of an input gene in the prediction of the target gene expression pattern is taken as an indication of a putative regulatory link.

dynGENIE3 : Extension of GENIE3 for time series data

::DEVELOPER

vân anh huynh-thu

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • MatLab / R Package

:: DOWNLOAD

 GENIE3 / dynGENIE3

:: MORE INFORMATION

Citation

Huynh-Thu VA, Geurts P.
dynGENIE3: dynamical GENIE3 for the inference of gene networks from time series expression data.
Sci Rep. 2018 Feb 21;8(1):3384. doi: 10.1038/s41598-018-21715-0. PMID: 29467401; PMCID: PMC5821733.

Inferring regulatory networks from expression data using tree-based methods
Huynh-Thu, V. A., Irrthum, A., Wehenkel, L., and Geurts, P.
PLoS ONE, 5(9):e12776, 2010.

PEDIBD – Pedigree IBD & Haplotype Inference

PEDIBD

:: DESCRIPTION

PEDIBD infers pairwise Infer identical-by-descent (IBD) and skips haplotype and inheritance construction

::DEVELOPER

Xin Li 

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux
  • MatLab

:: DOWNLOAD

  PEDIBD

:: MORE INFORMATION

Citation

J Comput Biol. 2011 Nov;18(11):1411-21. doi: 10.1089/cmb.2011.0167. Epub 2011 Sep 16.
Haplotype reconstruction in large pedigrees with untyped individuals through IBD inference.
Li X1, Li J.

CAPITAL 1.0.2 – Comparative Analysis of Pseudotime trajectory Inference with Tree ALignment

CAPITAL 1.0.2

:: DESCRIPTION

CAPITAL is a computational method for comparing pseudotime trajectories with tree alignment whereby trajectories including branchings can be automatically compared.

::DEVELOPER

Yuki Kato

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Python

:: DOWNLOAD

CAPITAL

:: MORE INFORMATION

Citation

Chaplin 1.2.3 – Case-control Haplotype Inference package

Chaplin 1.2.3

:: DESCRIPTION

Chaplin (Case-control haplotype inference package.) is a software program for identifying specific haplotypes or haplotype features that are associated with disease using genotype data from a case-control study.

::DEVELOPER

Epstein software

:: SCREENSHOTS

:: REQUIREMENTS

  • Windows

:: DOWNLOAD

   Chaplin

:: MORE INFORMATION

Citation

Epstein MP and Satten GA (2003).
Inference on haplotype effects in case-control studies using unphased genotype data.
Am. J. Hum. Genet. 73:1316-1329

Satten GA and Epstein MP (2004).
Comparison of prospective and retrospective methods for haplotype inference in case-control studies.
Genet Epidemiol. 2004 Nov; 27(3):192-201

HAPLO-IHP – Haplotype Inference using Identified Haplotype Patterns

HAPLO-IHP

:: DESCRIPTION

HaploIHP is a program for haplotype reconstruction using identified haplotypes and haplotype patterns

::DEVELOPER

Kui Zhang

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux
  • Perl

:: DOWNLOAD

 HaploIHP

:: MORE INFORMATION

Citation

Bioinformatics. 2007 Sep 15;23(18):2399-406. Epub 2007 Jul 21.
Haplotype inference for present-absent genotype data using previously identified haplotypes and haplotype patterns.
Yoo YJ1, Tang J, Kaslow RA, Zhang K.

SHIPS 1.1 – Spectral Hierarchical clustering for the Inference of Population Structure

SHIPS 1.1

:: DESCRIPTION

SHIPS is a non-parametric clustering algorithm that clusters individuals from a population into genetically homogeneous sub-populations from genotype data.

::DEVELOPER

Matthieu Bouaziz <matthieu.x.bouaziz@gmail.com>

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/ Windows/MacOsX
  • R package

:: DOWNLOAD

  SHIPS

:: MORE INFORMATION

Citation

PLoS One. 2012;7(10):e45685. doi: 10.1371/journal.pone.0045685. Epub 2012 Oct 12.
SHIPS: Spectral Hierarchical clustering for the Inference of Population Structure in genetic studies.
Bouaziz M, Paccard C, Guedj M, Ambroise C.

GenoClone 0.1 – subClone inference and studying Tumor Heterogenity

GenoClone 0.1

:: DESCRIPTION

GenoClone aims to provide useful tool to infer the tumor subclones and study tumor heterogeneity.

::DEVELOPER

Au Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

GenoClone

:: MORE INFORMATION

Citation

Zou M, Jin R, Au KF.
Revealing tumor heterogeneity of breast cancer by utilizing the linkage between somatic and germline mutations.
Brief Bioinform. 2019 Nov 27;20(6):2306-2315. doi: 10.1093/bib/bby084. PMID: 30239581; PMCID: PMC6954402.

sNMF 2.0 – Inference of Population Structure using Sparse Non-negative Matrix Factorization algorithms

sNMF 2.0

:: DESCRIPTION

sNMF (Sparse Non-negative Matrix Factorization) is a fast and efficient method for the inference of Admixture Coefficients.

::DEVELOPER

Eric Frichot

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • MacOsX / Linux

:: DOWNLOAD

 sNMF

:: MORE INFORMATION

Citation

Genetics. 2014 Apr;196(4):973-83. doi: 10.1534/genetics.113.160572. Epub 2014 Feb 4.
Fast and efficient estimation of individual ancestry coefficients.
Frichot E1, Mathieu F, Trouillon T, Bouchard G, François O.