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Differential NOMe-seq analysis

Bioconductor version: Release (3.19)

dinoR tests for significant differences in NOMe-seq footprints between two conditions, using genomic regions of interest (ROI) centered around a landmark, for example a transcription factor (TF) motif. This package takes NOMe-seq data (GCH methylation/protection) in the form of a Ranged Summarized Experiment as input. dinoR can be used to group sequencing fragments into 3 or 5 categories representing characteristic footprints (TF bound, nculeosome bound, open chromatin), plot the percentage of fragments in each category in a heatmap, or averaged across different ROI groups, for example, containing a common TF motif. It is designed to compare footprints between two sample groups, using edgeR's quasi-likelihood methods on the total fragment counts per ROI, sample, and footprint category.

Author: Michaela Schwaiger [aut, cre]

Maintainer: Michaela Schwaiger <michaela.schwaiger at>

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


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:

dinoR-vignette HTML R Script
Reference Manual PDF


biocViews Coverage, DifferentialMethylation, Epigenetics, MethylSeq, NucleosomePositioning, Sequencing, Software, Transcription
Version 1.0.0
In Bioconductor since BioC 3.19 (R-4.4) (< 6 months)
License MIT + file LICENSE
Depends R (>= 4.3.0), SummarizedExperiment
Imports BiocGenerics, circlize, ComplexHeatmap, cowplot, dplyr, edgeR, GenomicRanges, ggplot2, Matrix, methods, rlang, stats, stringr, tibble, tidyr, tidyselect
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Follow Installation instructions to use this package in your R session.

Source Package dinoR_1.0.0.tar.gz
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macOS Binary (x86_64) dinoR_1.0.0.tgz
macOS Binary (arm64) dinoR_1.0.0.tgz
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