GSMA 1.1 – Implementation of the Genome Search Meta-analysis Method

GSMA 1.1

:: DESCRIPTION

GSMA (Genome Scan Meta-Analysis) is a rank-based method to perform meta-analysis of genome-wide linkage studies. The genome is divided into equal length bins (eg 30cM). For each study, the maximum evidence for linkage within each bin is assessed, and then the bins ranked according to this information for linkage. For each bin, the ranks across studies are summed, and this summed rank forms the statistic to test for evidence of linkage within the bin. Significance is assessed using a distribution function (Wise et al, 1999), or by simulation (Levinson et al, 2003).

::DEVELOPER

Professor Cathryn Lewis’ Group

:: SCREENSHOTS

N/A

::REQUIREMENTS

Windows/Linux/MacOsX

:: DOWNLOAD

GSMA

:: MORE INFORMATION

Citation

Fabio Pardi et al.
GSMA: software implementation of the genome search meta-analysis method
Bioinformatics (2005) 21 (24): 4430-4431.

MLPERCEP 2.0 – Multiple Layer Perceptron Implementation for the Biological Problems

MLPERCEP 2.0

:: DESCRIPTION

MLPERCEP is a multiple layer perceptron implementation for the biological problems . For the researchers in Life science some utility programs are included for them to easily format there microarray and DNA sequence data.

::DEVELOPER

Jai Prakash Mehta

:: SCREENSHOTS

:: REQUIREMENTS

Windows
.net

:: DOWNLOAD

MLPERCEP

:: MORE INFORMATION

Regression tree package – Implementation of Ensembles of Multiple output Regression Trees

Regression tree package

:: DESCRIPTION

Regression tree package contains a c implementation of (multiple output) regression trees and various ensemble methods thereof, including extremely randomized trees (Geurts et al., 2006), Random Forests (Breiman, 2001), and multiple additive regression trees (Friedman et al.).

::DEVELOPER

Pierre Geurts

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux / Windows / MacOsX
MatLab

:: DOWNLOAD

Regression tree package

:: MORE INFORMATION