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qtlnet  

Causal Inference of QTL Networks
View on CRAN: Click here


Download and install qtlnet package within the R console
Install from CRAN:
install.packages("qtlnet")

Install from Github:
library("remotes")
install_github("cran/qtlnet")

Install by package version:
library("remotes")
install_version("qtlnet", "1.5.4")



Attach the package and use:
library("qtlnet")
Maintained by
Brian S. Yandell
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2012-06-08
Latest Update: 2020-04-13
Description:
Functions to Simultaneously Infer Causal Graphs and Genetic Architecture. Includes acyclic and cyclic graphs for data from an experimental cross with a modest number (<10) of phenotypes driven by a few genetic loci (QTL). Chaibub Neto E, Keller MP, Attie AD, Yandell BS (2010) Causal Graphical Models in Systems Genetics: a unified framework for joint inference of causal network and genetic architecture for correlated phenotypes. Annals of Applied Statistics 4: 320-339. .
How to cite:
Brian S. Yandell (2012). qtlnet: Causal Inference of QTL Networks. R package version 1.5.4, https://cran.r-project.org/web/packages/qtlnet. Accessed 08 Oct. 2026.
Previous versions and publish date:
(2026-07-09 06:46), 1.2.4 (2012-06-08 16:26), 1.2.5 (2012-06-25 20:16), 1.3.3 (2013-07-03 07:12), 1.3.5 (2013-09-16 20:55), 1.3.6 (2014-03-14 00:03), 1.4.4 (2018-04-05 23:50)
Other packages that cited qtlnet R package
View qtlnet citation profile
Other R packages that qtlnet depends, imports, suggests or enhances
Complete documentation for qtlnet
Functions, R codes and Examples using the qtlnet R package
Some associated functions: Pscdbp . acyclic . bic . cyclica . cyclicb . cyclicc . diag . generate . glxnet . igraph . loci . mcmc . parallel . parents . qdg . qdg.perm.test . sem . subset . summary . write . 
Some associated R codes: average.R . bic.R . cov.matrix.R . diag.R . generate.R . igraph.R . loci.R . lod.score.R . log.like.R . mcmc.R . parallel.R . perm.R . qdg.R . scanone.R . score.R . sem.R . solution.R . summary.R . write.R .  Full qtlnet package functions and examples
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