Bioc2026 Registration Open!

BUMHMM

Computational pipeline for computing probability of modification from structure probing experiment data

Bioconductor version: 3.23 · Package version: 1.36.0

This is a probabilistic modelling pipeline for computing per- nucleotide posterior probabilities of modification from the data collected in structure probing experiments. The model supports multiple experimental replicates and empirically corrects coverage- and sequence-dependent biases. The model utilises the measure of a "drop-off rate" for each nucleotide, which is compared between replicates through a log-ratio (LDR). The LDRs between control replicates define a null distribution of variability in drop-off rate observed by chance and LDRs between treatment and control replicates gets compared to this distribution. Resulting empirical p-values (probability of being "drawn" from the null distribution) are used as observations in a Hidden Markov Model with a Beta-Uniform Mixture model used as an emission model. The resulting posterior probabilities indicate the probability of a nucleotide of having being modified in a structure probing experiment.

Installation

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("BUMHMM")

Details

MaintainerAlina Selega <alina.selega@gmail.com>
AuthorAlina Selega (alina.selega@gmail.com), Sander Granneman, Guido Sanguinetti
LicenseGPL-3
Downloads rank484
Source branchRELEASE_3_23
biocViewsBayesian, Classification, Coverage, FeatureExtraction, GeneExpression, GeneRegulation, GeneticVariability, Genetics, HiddenMarkovModel, ImmunoOncology, RNASeq, Regression, Sequencing, Software, StructuralPrediction, Transcription, Transcriptomics

Documentation

Download

Follow the installation instructions to use this package in your R session.

Source packageBUMHMM_1.36.0.tar.gz
Windows binary (x86_64)BUMHMM_1.36.0.zip
macOS binary (arm64)BUMHMM_1.36.0.tgz
macOS binary (x86_64)BUMHMM_1.36.0.tgz
Dependencies

Depends: R (>= 3.5.0)

Imports: devtools, stringi, gtools, stats, utils, SummarizedExperiment, Biostrings, IRanges

Suggests: testthat, knitr, BiocStyle