AMARETTO
Bioc currentRegulatory Network Inference and Driver Gene Evaluation using Integrative Multi-Omics Analysis and Penalized Regression
Release Lineage
Entered 3.9 · May 3, 2019
Current · Requires R 4.6
Description
Integrating an increasing number of available multi-omics cancer data remains one of the main challenges to improve our understanding of cancer. One of the main challenges is using multi-omics data for identifying novel cancer driver genes. We have developed an algorithm, called AMARETTO, that integrates copy number, DNA methylation and gene expression data to identify a set of driver genes by analyzing cancer samples and connects them to clusters of co-expressed genes, which we define as modules. We applied AMARETTO in a pancancer setting to identify cancer driver genes and their modules on multiple cancer sites. AMARETTO captures modules enriched in angiogenesis, cell cycle and EMT, and modules that accurately predict survival and molecular subtypes. This allows AMARETTO to identify novel cancer driver genes directing canonical cancer pathways.
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
52 12 exported
Complexity
4.2 avg / 20 max
Call network
52 nodes / 42 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
3,992
Files
91
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
12
Internal functions
40
Recent export changes
Testing & CI
Has tests
Yes
Test-to-code ratio
0.03
testthat edition
–
CI present
No
CI type
[]
PR gated
No
Docs
Roxygen coverage
100%
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
50%
Unsafe pattern score
3
Dep constraint coverage
3.2%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
3.6
System requirements
–
C++ standard
–
License
Apache License (== 2.0) + file LICENSE
License flags
not SPDX, not OSI
History
Versions
15
First release
2019-05-02
Latest release
2026-04-28
Avg cadence
182 days
Cold removal rate
–
Dep drift
3
LOC over versions
Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.
Documentation
- Examples that run
- 83%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 0%
Topics
People
Olivier Gevaert
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("AMARETTO")Cite the R Observatory
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