XWAS-V2.0 (Old Version, May 2017)

XWAS (chromosome X-Wide Analysis toolSet) is a software suite for the analysis of the X chromosome in association analyses and similar studies.

Please note that this is an older version of our software. Visit the XWAS project's web page to find the current manual, download links, references, and related information for XWAS 3.0.

Downloads

   

XWAS version 2.0 begins with an optional sex-aware genotype calling pipeline for the X chromosome from raw intensity data based on an Affymetrix genotype array. The software then provides extensive QC procedures that are tailored to X. Followed is an optional imputation pipeline based on IMPUTE2. The software offers an array of statistical tests of association of X-linked markers, while correcting for population stratification based on EIGENSTRAT and controlling for any other covariates. 

The XWAS software package is implemented in C++ and scripts. It includes functions from PLINK. It is freely available for academic usage and offered open source. It is optimized for LINUX, but can be compiled for Windows and MAC OS.

Selected Recent Related Publications (How to Cite)

1. Please cite these papers if you use the basic QC or association methods:

Gao F, Chang D, Biddanda A, Ma L, Guo Y, Zhou Z, Keinan A. "XWAS: a toolset for genetic data analysis and association studies of the X chromosome." Journal of Heredity. 2015;106(5):6.

Chang D, Gao F, Slavney A, Ma L, Waldman Y, Sams A, Billing-Ross P, Madar A, Spritz R, Keinan A. "Accounting for eXentricities: Analysis of the X Chromosome in GWAS Reveals X-Linked Genes Implicated in Autoimmune Diseases.PLoS ONE. 2014;9(12):e113684.

2. Please cite this paper if you use the X-inactivation-based methods:

Ma L, Hoffman G, Keinan A. "X-inactivation informs variance-based testing for X-linked association of a quantitative trait." BMC Genomics. 2015;16:241.

3. Please cite this paper if you use gene-based tests for interaction:

Ma L, Clark AG, Keinan A. "Gene-based testing of interactions in association studies of quantitative traits."PLoS Genet.. 2013;9:e1003321