Package: mvMAPIT 2.0.3

Julian Stamp

mvMAPIT: Multivariate Genome Wide Marginal Epistasis Test

Epistasis, commonly defined as the interaction between genetic loci, is known to play an important role in the phenotypic variation of complex traits. As a result, many statistical methods have been developed to identify genetic variants that are involved in epistasis, and nearly all of these approaches carry out this task by focusing on analyzing one trait at a time. Previous studies have shown that jointly modeling multiple phenotypes can often dramatically increase statistical power for association mapping. In this package, we present the 'multivariate MArginal ePIstasis Test' ('mvMAPIT') – a multi-outcome generalization of a recently proposed epistatic detection method which seeks to detect marginal epistasis or the combined pairwise interaction effects between a given variant and all other variants. By searching for marginal epistatic effects, one can identify genetic variants that are involved in epistasis without the need to identify the exact partners with which the variants interact – thus, potentially alleviating much of the statistical and computational burden associated with conventional explicit search based methods. Our proposed 'mvMAPIT' builds upon this strategy by taking advantage of correlation structure between traits to improve the identification of variants involved in epistasis. We formulate 'mvMAPIT' as a multivariate linear mixed model and develop a multi-trait variance component estimation algorithm for efficient parameter inference and P-value computation. Together with reasonable model approximations, our proposed approach is scalable to moderately sized genome-wide association studies. Crawford et al. (2017) <doi:10.1371/journal.pgen.1006869>. Stamp et al. (2023) <doi:10.1093/g3journal/jkad118>.

Authors:Julian Stamp [cre, aut], Lorin Crawford [aut]

mvMAPIT_2.0.3.tar.gz
mvMAPIT_2.0.3.tar.gz(r-4.5-noble)mvMAPIT_2.0.3.tar.gz(r-4.4-noble)
mvMAPIT.pdf |mvMAPIT.html
mvMAPIT/json (API)
NEWS

# Install 'mvMAPIT' in R:
install.packages('mvMAPIT', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/lcrawlab/mvmapit/issues

Pkgdown:https://lcrawlab.github.io

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:
  • mvmapit_data - Multivariate MAPIT analysis and exhaustive search analysis.
  • phillips_data - Multivariate MAPIT analysis of binding affinities in broadly neutralizing antibodies.
  • simulated_data - Genotype and trait data with epistasis.

3.71 score 17 scripts 219 downloads 5 exports 53 dependencies

Last updated 1 years agofrom:0eada31faf. Checks:OK: 1 NOTE: 1. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 23 2024
R-4.5-linux-x86_64NOTENov 23 2024

Exports:cauchy_combinedfishers_combinedharmonic_combinedmvmapitsimulate_traits

Dependencies:backportsbriocallrcheckmateclicodetoolsCompQuadFormcpp11crayondescdiffobjdigestdplyrevaluatefansiFMStableforeachfsgenericsglueharmonicmeanpiteratorsjsonlitelifecycleloggingmagrittrmvtnormpillarpkgbuildpkgconfigpkgloadpraiseprocessxpspurrrR6RcppRcppArmadilloRcppParallelRcppProgressRcppSpdlogrlangrprojrootstringistringrtestthattibbletidyrtidyselectutf8vctrswaldowithr

Dockerized mvMAPIT

Rendered fromtutorial-docker-mvmapit.Rmdusingknitr::rmarkdownon Nov 23 2024.

Last update: 2022-12-05
Started: 2022-12-05

Empirical comparison of P-value combination methods in mvMAPIT

Rendered fromstudy-compare-p-value-combine-methods.Rmdusingknitr::rmarkdownon Nov 23 2024.

Last update: 2023-09-22
Started: 2023-09-22

Illustrating multivariate MAPIT with Simulated Data

Rendered frommvMAPIT.Rmdusingknitr::rmarkdownon Nov 23 2024.

Last update: 2023-09-22
Started: 2022-12-05

Joint modeling of hematology traits yields epistatic signal in stock of mice

Rendered fromstudy-wtccc-mice.Rmdusingknitr::rmarkdownon Nov 23 2024.

Last update: 2023-09-22
Started: 2022-12-05

Simulate Traits

Rendered fromtutorial-simulations.Rmdusingknitr::rmarkdownon Nov 23 2024.

Last update: 2022-12-05
Started: 2022-12-05

Synergistic epistasis in binding affinity landscapes

Rendered fromstudy-phillips-bnabs.Rmdusingknitr::rmarkdownon Nov 23 2024.

Last update: 2022-12-05
Started: 2022-12-05