BUMHMM

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

Bioconductor version: Release (3.5)

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.

Author: Alina Selega (alina.selega@gmail.com), Sander Granneman, Guido Sanguinetti

Maintainer: Alina Selega <alina.selega at gmail.com>

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("BUMHMM")

Documentation

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

browseVignettes("BUMHMM")

Details

Package Archives

Follow Installation instructions to use this package in your R session.