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HeritSeq  

Heritability of Gene Expression for Next-Generation Sequencing
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("HeritSeq", "1.0.2")



Attach the package and use:
library("HeritSeq")
Maintained by
W. Jenny Shi
[Scholar Profile | Author Map]
First Published: 2017-01-04
Latest Update: 2021-07-12
Description:
Statistical framework to analyze heritability of gene expression based on next-generation sequencing data and simulating sequencing reads. Variance partition coefficients (VPC) are computed using linear mixed effects and generalized linear mixed effects models. Compound Poisson and negative binomial models are included. Reference: Rudra, Pratyaydipta, et al. "Model based heritability scores for high-throughput sequencing data." BMC bioinformatics 18.1 (2017): 143.
How to cite:
W. Jenny Shi (2017). HeritSeq: Heritability of Gene Expression for Next-Generation Sequencing. R package version 1.0.2, https://cran.r-project.org/web/packages/HeritSeq. Accessed 29 Mar. 2025.
Previous versions and publish date:
1.0.0 (2017-01-04 10:56), 1.0.1 (2019-02-11 22:13)
Other packages that cited HeritSeq R package
View HeritSeq citation profile
Other R packages that HeritSeq depends, imports, suggests or enhances
Complete documentation for HeritSeq
Functions, R codes and Examples using the HeritSeq R package
Some associated functions: computeVPC.CP . computeVPC.NB . fit.CP . fit.NB . fitComputeVPC.lmer . getBootCI . getReadMatrix.CP . getReadMatrix.NB . para_cp . para_nb . simData . simData_voom . simData_vst . strains . weights_voom . 
Some associated R codes: HeriTools.R . data.R .  Full HeritSeq package functions and examples
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