Package: BUMHMM 1.29.0

Alina Selega

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

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.

Authors:Alina Selega, Sander Granneman, Guido Sanguinetti

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NEWS

# Install 'BUMHMM' in R:

install.packages('BUMHMM', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

covFile - Example coverage data set.
docFile - Example drop-off count data set.
dorFile - Example drop-off rate data set.
se - Example RNA structure probing data set.
seq - Example genomic sequence string.

On BioConductor:BUMHMM-1.29.0(bioc 3.20)BUMHMM-1.28.0(bioc 3.19)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

bioconductor-package

7 exports 0.82 score 117 dependencies 1 mentions

Last updated 2 months agofrom:deddba96ee

Exports:computeProbs computeStretches findPatternPos nuclPerm scaleDOR selectNuclPos stabiliseVariance

Dependencies:abind askpass base64enc Biobase BiocGenerics Biostrings brew brio bslib cachem callr cli clipr commonmark cpp11 crayon credentials curl DelayedArray desc devtools diffobj digest downlit ellipsis evaluate fansi fastmap fontawesome fs GenomeInfoDb GenomeInfoDbData GenomicRanges gert gh gitcreds glue gtools highr htmltools htmlwidgets httpuv httr httr2 ini IRanges jquerylib jsonlite knitr later lattice lifecycle magrittr Matrix MatrixGenerics matrixStats memoise mime miniUI openssl pillar pkgbuild pkgconfig pkgdown pkgload praise prettyunits processx profvis promises ps purrr R6 ragg rappdirs rcmdcheck Rcpp rematch2 remotes rlang rmarkdown roxygen2 rprojroot rstudioapi rversions S4Arrays S4Vectors sass sessioninfo shiny sourcetools SparseArray stringi stringr SummarizedExperiment sys systemfonts testthat textshaping tibble tinytex UCSC.utils urlchecker usethis utf8 vctrs waldo whisker withr xfun xml2 xopen xtable XVector yaml zip zlibbioc

An Introduction to the BUMHMM pipeline

Rendered fromBUMHMM.Rnwusingknitr::knitron Jun 15 2024.

Last update: 2016-11-22
Started: 2016-10-23

Help page	Topics
Function to compute posterior probabilities of modification with the BUM-HMM model for all nucleotides.	computeProbs
Function to compute continuous stretches of nucleotide positions.	computeStretches
Example coverage data set.	covFile
Example drop-off count data set.	docFile
Example drop-off rate data set.	dorFile
Function to find positions of the nucleotide patterns in the sequence.	findPatternPos
Function to create nucleobase patterns.	nuclPerm
Function to scale drop-off rates across replicates to a common median.	scaleDOR
Example RNA structure probing data set.	se
Function to compute selections of nucleotide positions.	selectNuclPos
Example genomic sequence string.	seq
Function to reduce variance of LDRs as a function of coverage.	stabiliseVariance

Package: BUMHMM 1.29.0

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

An Introduction to the BUMHMM pipeline

Citation

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Help Manual

Usage by other packages (reverse dependencies)