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Is designed to test for association between methylation at CpG sites across the genome and a phenotype of interest, adjusting for any relevant covariates. The package can perform standard analyses of large datasets very quickly with no need to impute the data. It can also handle mixed effects models with chip or batch entering the model as a random intercept. Also includes tools to apply quality control filters, perform permutation tests, and create QQ plots, manhattan plots, and scatterplots for individual CpG sites.
Version: | 2.70 |
Depends: | R (≥ 2.10), nlme, methods |
Published: | 2024-07-16 |
DOI: | 10.32614/CRAN.package.CpGassoc |
Author: | Barfield, R., Conneely, K., Kilaru,V |
Maintainer: | R Barfield <barfieldrichard8 at gmail.com> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: | no |
In views: | MixedModels |
CRAN checks: | CpGassoc results |
Reference manual: | CpGassoc.pdf |
Vignettes: |
CpGassoc reference |
Package source: | CpGassoc_2.70.tar.gz |
Windows binaries: | r-devel: CpGassoc_2.70.zip, r-release: CpGassoc_2.70.zip, r-oldrel: CpGassoc_2.70.zip |
macOS binaries: | r-release (arm64): CpGassoc_2.70.tgz, r-oldrel (arm64): CpGassoc_2.70.tgz, r-release (x86_64): CpGassoc_2.70.tgz, r-oldrel (x86_64): CpGassoc_2.70.tgz |
Old sources: | CpGassoc archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.