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DESCRIPTION
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DESCRIPTION
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Package: BUMHMM
Type: Package
Title: Computational pipeline for computing probability of modification
from structure probing experiment data
Version: 1.27.0
Date: 2021-11-20
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: ImmunoOncology, GeneticVariability, Transcription, GeneExpression,
GeneRegulation, Coverage, Genetics, StructuralPrediction,
Transcriptomics, Bayesian, Classification, FeatureExtraction,
HiddenMarkovModel, Regression, RNASeq, Sequencing