Forward is a bioinformatics utility to execute, manage and explore phenomic studies. It’s documentation is available here. An issue tracker for this project (which can be used for feature requests) is also available.


genipe is an automatic pipeline to perform genome-wide imputation analysis on a genotyped dataset. Full documentation is available here, and installation instruction here and in the README file.



pyplink is an open source python module that enables working with Plink binary files without having to first convert them to text file. The README file contains a description of how to use this module.



pyGenClean is a bioinformatics tool to facilitate and standardize the genetic data clean up pipeline with genotyping array data. In conjuction with a source batch-queuing system, the tool minimizes data manipulation errors, it accelerates the completion of the data clean up process and it provides informative graphics and metrics to guide decision making for statistical analysis.


CNV Analysis Toolkit

This set of tools was created for the study of whole genome sequencing based algorithms for CNV genotyping in monozygotic twins families.



We have created a scritp that converts integrated SNP and CNV calls generated from Birdsuite’s Fawkes procedure into phased copy number genotypes (CN genotypes) using familial pedigree data. This software makes possible the use of CNPs and CNVs for genetic linkage with family data.



We have created a program that automatically generates the input files for Alohomora_m. The program Chip2Spell takes as input a genotype report and publicly available annotation files and creates the genotype file, map file and frequency file that will be used by Alohomora. The program is especially useful if the map and frequency files for a given plateform are not stored in the Alohomora library, but it is also a quick way to convert the standard Affymetrix or Illumina genotype report format to the AB format requested by Alohomora.


Gene-environment interactions

We have created some code that perform a GWAS analysis of gene-environnement interactions for imputed SNPs and non-imputed SNPs. Instead of using PLINK to perform the logistic regressions or the generalized linear model, we used the PLINK’s R plug-in function to do it for the non-imputed SNPs.


MAX test

We have coded the MAX test of Zheng and Gastwirth (Statist. Med. 2006;25:3150) in some SAS MACROS. As well, we have created a wrapper for our MAX test code that allows the user to correct for multiple testing by using the maxT algorithm ( Alg 4.1 of Westfall and Young, 1993).

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