Package: BUMHMM
Type: Package
Title: Computational pipeline for computing probability of modification
        from structure probing experiment data
Version: 1.2.0
Date: 2016-09-22
Author: Alina Selega (alina.selega@gmail.com), Sander Granneman, Guido
        Sanguinetti
Maintainer: Alina Selega <alina.selega@gmail.com>
Description: 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.
Depends: R (>= 3.4)
License: GPL-3
Imports: devtools, stringi, gtools, stats, utils, SummarizedExperiment,
        Biostrings, IRanges
Suggests: testthat, knitr, BiocStyle
VignetteBuilder: knitr
LazyData: true
biocViews: GeneticVariability, Transcription, GeneExpression,
        GeneRegulation, Coverage, Genetics, StructuralPrediction,
        Transcriptomics, Bayesian, Classification, FeatureExtraction,
        HiddenMarkovModel, Regression, RNASeq, Sequencing
NeedsCompilation: no
Packaged: 2017-10-31 01:59:34 UTC; biocbuild
Built: R 3.4.2; ; 2017-10-31 03:18:41 UTC; windows
