dinoR
Differential NOMe-seq analysis
Bioconductor version: 3.23 · Package version: 1.8.0
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.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("dinoR") Details
| Maintainer | Michaela Schwaiger <michaela.schwaiger@fmi.ch> |
| Author | Michaela Schwaiger [aut, cre] (ORCID: <https://orcid.org/0000-0002-4522-7810>) |
| License | MIT + file LICENSE |
| URL | https://github.com/xxxmichixxx/dinoR |
| Bug Reports | https://github.com/xxxmichixxx/dinoR/issues |
| Downloads rank | 187 |
| Source branch | RELEASE_3_23 |
| biocViews | Coverage, DifferentialMethylation, Epigenetics, MethylSeq, NucleosomePositioning, Sequencing, Software, Transcription |
Documentation
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Dependencies
Depends: R (>= 4.3.0), SummarizedExperiment
Imports: BiocGenerics, circlize, ComplexHeatmap, cowplot, dplyr, edgeR, GenomicRanges, ggplot2, Matrix, methods, rlang, stats, stringr, tibble, tidyr, tidyselect
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)