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Fit Penalised Generalised Least Squares models

Bioconductor version: Release (3.19)

Combine generalised least squares methodology from the nlme package for dealing with autocorrelation with penalised least squares methods from the glmnet package to deal with high dimensionality. This pengls packages glues them together through an iterative loop. The resulting method is applicable to high dimensional datasets that exhibit autocorrelation, such as spatial or temporal data.

Author: Stijn Hawinkel [cre, aut]

Maintainer: Stijn Hawinkel <stijn.hawinkel at>

Citation (from within R, enter citation("pengls")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

Vignette of the pengls package HTML R Script
Reference Manual PDF


biocViews Regression, Software, Spatial, TimeCourse, Transcriptomics
Version 1.10.0
In Bioconductor since BioC 3.14 (R-4.1) (2.5 years)
License GPL-2
Depends R (>= 4.2.0)
Imports glmnet, nlme, stats, BiocParallel
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Suggests knitr, rmarkdown, testthat
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Follow Installation instructions to use this package in your R session.

Source Package pengls_1.10.0.tar.gz
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macOS Binary (x86_64) pengls_1.10.0.tgz
macOS Binary (arm64) pengls_1.10.0.tgz
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Source Repository (Developer Access) git clone
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