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Protocols

FastEpistasis specifications

Information


Unique identifier OMICS_10119
Name FastEpistasis
Software type Package/Module
Interface Command line interface
Restrictions to use Academic or non-commercial use
Operating system Unix/Linux
Parallelization MPI
Computer skills Advanced
Version 2.05
Stability Stable
Maintained Yes

Versioning


No version available

Maintainer


  • person_outline Thierry Schüpbach

Publication for FastEpistasis

FastEpistasis citations

 (9)
library_books

Effect of genetic architecture on the prediction accuracy of quantitative traits in samples of unrelated individuals

2018
Heredity
PMCID: 5943287
PMID: 29426878
DOI: 10.1038/s41437-017-0043-0

[…] ariants with P-values for association smaller than 10−3, 10−5, 10−7, and 10−9 to build the additive GRM to use in the prediction analysis.We also performed a pairwise interaction GWAS (EpiGWAS) using FastEpistasis (Schüpbach et al. ), testing all possible 18,7952 variant-variant combinations on the pruned genotype data described in the previous section. We used the pruned genotype data here becaus […]

call_split

Exhaustive Genome Wide Search for SNP SNP Interactions Across 10 Human Diseases

2016
PMCID: 4938657
PMID: 27185397
DOI: 10.1534/g3.116.028563
call_split See protocol

[…] , a random selection of approximately 10,000 SNPs was obtained from each condition-specific dataset, and all possible pairs of SNPs (approximately 5 × 107 pairs) were tested for interaction using the FastEpistasis analytical approach (described below). Observed vs. expected-under-the-null −log P-values were plotted, and no evidence of inflation was observed (Figure S1; shown only for the discovery […]

library_books

Accounting for Genetic Architecture Improves Sequence Based Genomic Prediction for a Drosophila Fitness Trait

2015
PLoS One
PMCID: 4423967
PMID: 25950439
DOI: 10.1371/journal.pone.0126880

[…] as fixed effects and taking residuals from the fitted model []. Finally we performed a full genome-wide screen for pairwise interactions, fitting models of form Y = μ + V A + V B + V A×V B + ε, using FastEpistasis []. After the single marker and epistatic GWA analyses, we selected the top trait-associated additive variants and/or epistatic pairs with p < 10-X in the respective training set to cons […]

call_split

Filter free exhaustive odds ratio based genome wide interaction approach pinpoints evidence for interaction in the HLA region in psoriasis

2015
BMC Genet
PMCID: 4341885
PMID: 25655172
DOI: 10.1186/s12863-015-0174-3
call_split See protocol

[…] e purposes of this study, we excluded 3,521,114 SNP pairs with a total count of less than 50 in any row, or less than 5 in any cell of the contingency table. In addition to FORCE, we performed PLINK (FastEpistasis mode) on the top-ranked 500 pairs to compare the results obtained with both methods. […]

call_split

Analysis pipeline for the epistasis search – statistical versus biological filtering

2014
Front Genet
PMCID: 4012196
PMID: 24817878
DOI: 10.3389/fgene.2014.00106
call_split See protocol

[…] proach has been implemented in the epistasis module of PLINK () to test pair-wise diallelic by diallelic epistasis for both quantitative and binary traits. An extension of the PLINK epistasis module, FastEpistasis, uses an efficient parallel computation algorithm to test pair-wise interactions. FastEpistasis is 15 times faster than PLINK using a single core computer (). proposed an approach for j […]

call_split

Discovering epistasis in large scale genetic association studies by exploiting graphics cards

2013
Front Genet
PMCID: 3848199
PMID: 24348518
DOI: 10.3389/fgene.2013.00266
call_split See protocol

[…] elation matrices XijT Xij for any SNP pair i and j as shown in Equation (4) can simply be extracted from ATA and re-used in computing Equation (2). In benchmarks against the serial version of PLINK's FastEpistasis option (Purcell et al., ), the authors consistently reported speedups of around 2000x over a range of sample sizes.Source code, documentation, and test data is available and can be compi […]


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FastEpistasis institution(s)
Vital-IT Group, Swiss Institute of Bioinformatics, Lausanne, Switzerland; Molecular Modeling Group, Swiss Institute of Bioinformatics, Lausanne, Switzerland; Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland
FastEpistasis funding source(s)
Swiss Institute of Bioinformatics service grant; Swiss National Science Foundation grant #3100AO-116323/1

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