is a software for genome-wide interaction analysis (GWIA) of
case-control SNP data and quantitative traits. SNPs are selected for
joint analysis using a priori information. Sources of information to
define meaningful strategies can be statistical evidence
(single marker association at a moderate level, computed from the own
data) and genetic/biologic relevance (genomic
location, function class or pathway information).
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New Version: v1.15 (22 January
To compile INTERSNP-RARE, change #RARE 0 to #RARE 1 in intersnp.cpp.
- Methods for stratified analysis
- Output of the covariance matrix for
regression models to enable meta-analysis
of GWAS results.
- Regression rare variant association tests
- Adaptive permutation testing
- Streamlined and simplified bin
- Compatibility with SetID files. Ability
to create SetID
files from interval files.
- Gene reference interval file updated to Ensembl Release
Our software product INTERSNP implements:
- A logistic regression framework as well as
log-linear models for joint analysis of multiple SNPs
- All PLINK input formats (ped/map, tped/tfam, bed/bim/fam) can be used
- Automatic handling of SNP annotation and
- Methods to account for multiple testing, in
particular, Monte-Carlo simulations to judge genome-wide significance
- A linear regression framework for analysis of
- Pathway Association Analysis (SNP ratio,
Fisher score, Gene ratio, Fisher Max, Fisher MaxPlus)
- Genome-wide Haplotype Analysis
- Pre-tests for quick analysis
- Pathway Association Analysis with interaction-ratio
- ... and more
INTERSNP started as a project of the Institute f. Medical Biometry,
Informatics and Epidemiology, University of Bonn, Germany, and is now
maintained and extended by the AG Genomic Mathematics in
Neuroepidemiology at the German Center for Neurodegenerative Diseases,
Herold C, Steffens M, Brockschmidt FF, Baur MP, Becker T (2009) INTERSNP: Genome-wide Interaction Analysis Guided by a priori Information. Bioinformatics. 2009 Dec 15;25(24):3275-81
Herold C, Mattheisen M, Lacour A, Vaitsiakhovich T, Angisch M, Drichel D, Becker T (2012) Integrated genome-wide pathway association analysis with INTERSNP. Hum Hered. 2012;73(2):63-72.
Herold C, Ramirez A, Drichel D, Lacour A, Vaitsiakhovich T, Noethen MM, Jessen F, Maier W, Becker T (2013) A one-degree-of-freedom test for supra-multiplicativity of SNP effects. PLoS One. 2013 Oct 30;8(10):e78038.
Drichel D, Herold C, Lacour A, Ramirez A, Jessen F, Maier W, Noethen MM, Leber M, Vaitsiakhovich T, Becker T (2014) Rare variant testing of imputed data: an analysis pipeline typified. Hum Hered. 2014;78(3-4):164-78.