Anna L. Tyler, Wei Lu, Justin J. Hendrick, Vivek M. Philip, and Greg W. Carter
This package combines complementary information across multiple related phenotypes to infer directed epistatic interactions between genetic markers. The analysis in this package can be applied to a variety of engineered and natural populations.
corpcor, evd, qpcR, Matrix, igraph, fdrtool

corpcor, evd, qpcR, Matrix, igraph, fdrtool, shape

Combined Analysis of Pleiotropy and Epistasis
Anna L. Tyler, Wei Lu, Justin J. Hendrick, Vivek M. Philip, and Greg W.
Carter
Combines complementary information across multiple related
phenotypes to infer directed epistatic interactions between genetic markers.
This analysis can be applied to a variety of engineered and natural populations.
grDevices, graphics, stats, utils, corpcor, evd, qpcR, Matrix,
igraph, fdrtool, shape, parallel, doParallel, RColorBrewer,
foreach, HardyWeinberg, regress

grDevices, graphics, stats, utils, corpcor, evd, qpcR, Matrix,
igraph, fdrtool, shape, doParallel, RColorBrewer, foreach,
HardyWeinberg, regress

Combined Analysis of Pleiotropy and Epistasis for Diversity
Outbred Mice
c(
person("Anna", "Tyler", role = c("aut", "cre"), email = "anna.tyler@jax.org"),
person("Jake", "Emerson", role = c("aut"), email = "jake.emerson@jax.org"),
person("Baha", "El Kassaby", role = c("aut")),
person("Ann", "Wells", role = c("aut"), email = "ann.wells@jax.org"),
person("Georgi", "Kolishovski", role = c("aut")),
person("Vivek", "Philip", role = c("aut")),
person("Gregory", "Carter", role = c("aut")))
Combined Analysis of Pleiotropy and Epistasis infers predictive
networks between genetic variants and phenotypes. It can be used with
standard two-parent populations as well as multi-parent populations, such
as the Diversity Outbred (DO) mice, Collaborative Cross (CC) mice, or the
multi-parent advanced generation intercross (MAGIC) population of Arabidopsis
thaliana. It uses complementary information of pleiotropic gene variants across
different phenotypes to resolve models of epistatic interactions between alleles.
To do this, cape reparametrizes main effect and interaction coefficients from
pairwise variant regressions into directed influence parameters. These
parameters describe how alleles influence each other, in terms of suppression
and enhancement, as well as how gene variants influence phenotypes. All of the
final interactions are reported as directed interactions between pairs of
parental alleles. For detailed descriptions of the methods used in this package
please see the following references.
Carter, G. W., Hays, M., Sherman, A. & Galitski, T. (2012) <doi:10.1371/journal.pgen.1003010>.
Tyler, A. L., Lu, W., Hendrick, J. J., Philip, V. M. & Carter, G. W. (2013) <doi:10.1371/journal.pcbi.1003270>.
testthat (>= 2.3.2), knitr (>= 1.29), rmarkdown
abind, caTools, corpcor, doParallel, evd, foreach, here,
igraph, Matrix, parallel, pheatmap, propagate, qtl, qtl2,
qtl2convert, R6 (>= 2.4.1), RColorBrewer (>= 1.1-2), regress
(>= 1.3-21), shape (>= 1.4.5), stats, stringr (>= 1.4.0),
tools, utils, yaml (>= 2.2.1)
Anna Tyler [aut, cre],
Jake Emerson [aut],
Baha El Kassaby [aut],
Ann Wells [aut],
Georgi Kolishovski [aut],
Vivek Philip [aut],
Gregory Carter [aut]