Package: PQLseq 1.2.1

Jiaqiang Zhu

PQLseq: Efficient Mixed Model Analysis of Count Data in Large-Scale Genomic Sequencing Studies

An efficient tool designed for differential analysis of large-scale RNA sequencing (RNAseq) data and Bisulfite sequencing (BSseq) data in the presence of individual relatedness and population structure. 'PQLseq' first fits a Generalized Linear Mixed Model (GLMM) with adjusted covariates, predictor of interest and random effects to account for population structure and individual relatedness, and then performs Wald tests for each gene in RNAseq or site in BSseq.

Authors:Shiquan Sun, Jiaqiang Zhu, Xiang Zhou

PQLseq_1.2.1.tar.gz
PQLseq_1.2.1.tar.gz(r-4.5-noble)PQLseq_1.2.1.tar.gz(r-4.4-noble)
PQLseq_1.2.1.tgz(r-4.4-emscripten)PQLseq_1.2.1.tgz(r-4.3-emscripten)
PQLseq.pdf |PQLseq.html✨
PQLseq/json (API)

# Install 'PQLseq' in R:
install.packages('PQLseq', repos = 'https://cloud.r-project.org')
Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblascppopenmp

1.60 score 211 downloads 4 mentions 1 exports 8 dependencies

Last updated 4 years agofrom:0463c810bc. Checks:1 OK, 2 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 15 2025
R-4.5-linux-x86_64NOTEMar 15 2025
R-4.4-linux-x86_64NOTEMar 15 2025

Exports:pqlseq

Dependencies:codetoolsdoParallelforeachiteratorslatticeMatrixRcppRcppArmadillo

Citation

To cite package ‘PQLseq’ in publications use:

Sun S, Zhu J, Zhou X (2021). PQLseq: Efficient Mixed Model Analysis of Count Data in Large-Scale Genomic Sequencing Studies. R package version 1.2.1, https://CRAN.R-project.org/package=PQLseq.

ATTENTION: This citation information has been auto-generated from the package DESCRIPTION file and may need manual editing, see ‘help("citation")’.

Corresponding BibTeX entry: 

  @Manual{,
    title = {PQLseq: Efficient Mixed Model Analysis of Count Data in
      Large-Scale Genomic Sequencing Studies},
    author = {Shiquan Sun and Jiaqiang Zhu and Xiang Zhou},
    year = {2021},
    note = {R package version 1.2.1},
    url = {https://CRAN.R-project.org/package=PQLseq},
  }