BUMHMM
Bioc currentComputational pipeline for computing probability of modification from structure probing experiment data
Release Lineage
Entered 3.5 · Apr 25, 2017
Current · Requires R 4.6
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.
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
14 7 exported
Complexity
6.9 avg / 19 max
Call network
14 nodes / 8 edges
Test coverage is not measured for Bioconductor packages; nodes fall back to a neutral fill.
Call graph
Open call graph →Lowest coverage
Per-function coverage is not measured for this package yet.
Code
Structure
Lines of code
3,729
Files
51
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
7
Internal functions
7
Recent export changes
Testing & CI
Has tests
Yes
Test-to-code ratio
0.41
testthat edition
–
CI present
No
CI type
[]
PR gated
No
Docs
Roxygen coverage
100%
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
–
Unsafe pattern score
0
Dep constraint coverage
0%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
3.4
System requirements
–
C++ standard
–
License
GPL-3
License flags
SPDX valid, OSI approved
History
Versions
19
First release
2017-04-24
Latest release
2026-04-28
Avg cadence
182 days
Cold removal rate
–
Dep drift
0
LOC over versions
Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.
Documentation
- Examples that run
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 100%
Topics
People
Alina Selega
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("BUMHMM")Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
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