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HeritSeq (version 1.0.2)

Heritability of Gene Expression for Next-Generation Sequencing

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.

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Version

Install

install.packages('HeritSeq')

Monthly Downloads

178

Version

1.0.2

License

GPL-2

Maintainer

W. Shi

Last Published

July 12th, 2021

Functions in HeritSeq (1.0.2)

getReadMatrix.NB

Simulate a count matrix from negative binomial mixed effect models (NBMM).
fit.NB

Fit negative binomial mixed models (NBMM) for one or more features.
getBootCI

Compute variance partition coefficition (VPC) confidence intervals (CI) for one or more features.
computeVPC.NB

Calculate the negative binomial (NB) variance partition coefficient (VPC) for one or more features.
getReadMatrix.CP

Simulate a read matrix from compound Poisson mixed effect models (CPMM).
fitComputeVPC.lmer

Fit linear mixed models (LMM) and compute the VPC values for one or more features.
computeVPC.CP

Calculate the compound Poisson (CP) variance partition coefficient (VPC) for one or more features.
fit.CP

Fit compound Poisson mixed effect models (CPMM) for one or more features.
para_cp

Parameter matrix obtained from simData by fitting CPMM.
para_nb

Parameter matrix obtained from simData by fitting NBMM.
weights_voom

Weights used in the voom transformation.
simData_voom

Voom transformed version of simData.
simData

A simulated sequencing dataset.
strains

List of strain names for the samples.
simData_vst

Variance stabilize transformed version of simData.