Catapult – Associating new Genes with Traits, Phenotypes, and Diseases

Catapult

:: DESCRIPTION

Catapult (Combining dATa Across species using Positive-Unlabeled Learning Techniques), is a supervised machine learning method that uses a biased support vector machine where the features are derived from walks in a heterogeneous gene-trait network.

::DEVELOPER

the Marcotte Lab at University of Texas at Austin

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 Catapult

:: MORE INFORMATION

Citation:

Prediction and validation of gene-disease associations using methods inspired by social network analyses.
Singh-Blom UM, Natarajan N, Tewari A, Woods JO, Dhillon IS, Marcotte EM.
PLoS One. 2013 May 1;8(5):e58977. doi: 10.1371/journal.pone.0058977.

WAFFECT 1.2 – A package to Simulate Constrained Phenotypes under Disease model H1

WAFFECT 1.2

:: DESCRIPTION

WAFFECT (pronounced ‘double-u affect’ for ‘weighted affectation’) is a package to simulate phenotypic (case or control) datasets under a disease model H1 such that the total number of cases is constant across all the simulations (the constrain in the title).

::DEVELOPER

Gregory Nuel

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows
  • R

:: DOWNLOAD

 WAFFECT

:: MORE INFORMATION

Citation

Hum Hered. 2012;73(2):95-104. doi: 10.1159/000336194. Epub 2012 Mar 28.
Alternative methods for H1 simulations in genome-wide association studies.
Perduca V, Sinoquet C, Mourad R, Nuel G.