deepSNV
Bioc currentDetection of subclonal SNVs in deep sequencing data.
Release Lineage
Entered 2.10 · Apr 2, 2012
Current · Requires R 4.6
Description
This package provides provides quantitative variant callers for detecting subclonal mutations in ultra-deep (>=100x coverage) sequencing experiments. The deepSNV algorithm is used for a comparative setup with a control experiment of the same loci and uses a beta-binomial model and a likelihood ratio test to discriminate sequencing errors and subclonal SNVs. The shearwater algorithm computes a Bayes classifier based on a beta-binomial model for variant calling with multiple samples for precisely estimating model parameters - such as local error rates and dispersion - and prior knowledge, e.g. from variation data bases such as COSMIC.
None published for Bioconductor
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
38 13 exported
Complexity
3 avg / 8 max
Call network
38 nodes / 29 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
4,584
Files
74
Compiled share
6.2%
Has compiled src
Yes
Language breakdown
API
Exported functions
13
Internal functions
15
Testing
Has tests
No
Test-to-code ratio
0.00
testthat edition
–
Docs
Roxygen coverage
100%
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
0%
Unsafe pattern score
0
Dep constraint coverage
10%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
2.13.0
System requirements
1 externalGNU make
C++ standard
–
License
GPL-3
License flags
SPDX valid, OSI approved
History
Versions
29
First release
2012-04-13
Latest release
2026-04-28
Avg cadence
183 days
Cold removal rate
100%
Dep drift
5
LOC over versions
Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.
Documentation
- Help pages
- 35includes a package overview page
- Examples that run
- 93%26 run in a plain check · 2 hold no code
- Exported functions with examples
- 54%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 6%
Repository practices
Checks read the Bioconductor git repository (git.bioconductor.org), branch RELEASE_3_23.
1 practice detected in the Bioconductor git repository
Datasets
Topics
Depended on by (1)
Bioconductor (1)
Suggested by (1)
People
- Moritz Gerstung author maintainer
- Raul Alcantara contributor
- Niko Beerenwinkel thesis advisor
- David Jones contributor
- John Marshall contributor
- Inigo Martincorena contributor
Cite
Cite this package
Run in R for the authors' entry:
citation("deepSNV")The package provides a citation file, so citation() returns the authors' own entry.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-24, which the citation names so these numbers can be found later. More on citing and the projects behind them.