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Time-course differential gene expression data analysis using spline regression models followed by gene association network reconstruction

Bioconductor version: Release (3.19)

This package provides functions for differential gene expression analysis of gene expression time-course data. Natural cubic spline regression models are used. Identified genes may further be used for pathway enrichment analysis and/or the reconstruction of time dependent gene regulatory association networks.

Author: Agata Michna

Maintainer: Herbert Braselmann <hbraselmann at>, Martin Selmansberger <martin.selmansberger at>

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


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:

splineTimeR PDF R Script
Reference Manual PDF


biocViews DifferentialExpression, GeneExpression, GeneSetEnrichment, GraphAndNetwork, NetworkEnrichment, NetworkInference, Regression, Software, TimeCourse
Version 1.32.0
In Bioconductor since BioC 3.3 (R-3.3) (8 years)
License GPL-3
Depends R (>= 3.3), Biobase, igraph, limma, GSEABase, gtools, splines, GeneNet (>= 1.2.13), longitudinal (>= 1.1.12), FIs
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Follow Installation instructions to use this package in your R session.

Source Package splineTimeR_1.32.0.tar.gz
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macOS Binary (x86_64) splineTimeR_1.32.0.tgz
macOS Binary (arm64) splineTimeR_1.32.0.tgz
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Source Repository (Developer Access) git clone
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