Package: smer 0.0.3

Julian Stamp

smer: Sparse Marginal Epistasis Test

The Sparse Marginal Epistasis Test is a computationally efficient genetics method which detects statistical epistasis in complex traits; see Stamp et al. (2025, <doi:10.1101/2025.01.11.632557>) for details.

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

smer_0.0.3.tar.gz
smer_0.0.3.zip(r-4.7-x86_64)smer_0.0.3.zip(r-4.7-arm64)smer_0.0.3.zip(r-4.6-x86_64)smer_0.0.3.zip(r-4.6-arm64)
smer_0.0.3.tar.gz(r-4.7-arm64)smer_0.0.3.tar.gz(r-4.7-x86_64)smer_0.0.3.tar.gz(r-4.6-arm64)smer_0.0.3.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
smer/json (API)

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

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

Pkgdown/docs site:https://lcrawlab.github.io

Uses libs:
  • curl– Easy-to-use client-side URL transfer library
  • openssl– Secure Sockets Layer toolkit
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:

On CRAN:

Conda:

genomewideassociationepistasisgeneticssnplinearmixedmodelcurlopensslcppopenmp

3.48 score 9 scripts 649 downloads 6 exports 71 dependencies

Last updated from:3566b7170c. Checks:9 OK, 1 FAIL. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK203
linux-devel-x86_64OK224
source / vignettesOK344
linux-release-arm64OK200
linux-release-x86_64OK273
windows-devel-arm64OK343
windows-devel-x86_64OK347
windows-release-arm64OK355
windows-release-x86_64OK302
wasm-releaseFAIL196

Exports:approximate_memory_requirementscreate_hdf5_fileread_hdf5_datasetsimulate_traitssmewrite_hdf5_dataset

Dependencies:backportsBHbiocmakebitbit64briocallrcheckmateclicliprcodetoolsCompQuadFormcpp11crayondescdiffobjdir.expirydplyrevaluatefilelockFMStableforeachfsgenericsgenioglueharmonicmeanpHighFivehmsiteratorsjsonlitelifecycleloggingmagrittrmvMAPITmvtnormotelpillarpkgbuildpkgconfigpkgloadpraiseprettyunitsprocessxprogresspspurrrR6RcppRcppArmadilloRcppEigenRcppParallelRcppProgressRcppSpdlogreadrRhdf5librlangrprojrootstringistringrtestthattibbletidyrtidyselecttruncnormtzdbutf8vctrsvroomwaldowithr

How To Use the Sparse Marginal Epistasis Test
Run SME with PLINK data | Data Requirements and File Formats | Specifying SNPs for Analysis | Understanding the Results | Visualizing Genomic Associations | Understanding Variance Components and Effect Sizes | Narrow Sense Heritability Estimates | SessionInfo
Rendered fromsmer.Rmdusingknitr::rmarkdown

Last update: 2025-08-22
Started: 2025-01-16

Conditioning Epistasis Search on Open Chromatin
DNAse I hypersensitive sites of erythroid differentiation reveal statistical epistasis in human hematology traits | Mask File Preparation | References | SessionInfo
Rendered fromstudy-erythroid-differentiation-data.Rmdusingknitr::rmarkdown

Last update: 2025-01-16
Started: 2025-01-16

How To Cite Our Work
The Sparse Marginal Epistasis Test (SME) | The multivariate Marginal Epistasis Test (mvMAPIT) | The Marginal Epistasis Test (MAPIT)
Rendered fromtutorial-cite-us.Rmdusingknitr::rmarkdown

Last update: 2025-01-16
Started: 2025-01-16

How To Create a Mask File
Mask File Format | Mask Format Requirements | Creating and Using Mask Files | SessionInfo
Rendered fromtutorial-create-mask-file.Rmdusingknitr::rmarkdown

Last update: 2025-01-16
Started: 2025-01-16

How To Optimize the Memory Requirements of SME
Genotype Data Size and Number of Blocks | Number of Random Vectors | Number of SNPs Sharing Random Vectors | Genotype Masking for the Gene-by-Gene Interaction Covariance | Explore the Memory Requirements | A Note on the Runtime of SME | SessionInfo
Rendered fromtutorial-memory-optimization.Rmdusingknitr::rmarkdown

Last update: 2025-01-16
Started: 2025-01-16

How To Simulate Traits
SessionInfo
Rendered fromtutorial-simulate-traits.Rmdusingknitr::rmarkdown

Last update: 2025-01-16
Started: 2025-01-16