anota2seq
Bioc currentGenerally applicable transcriptome-wide analysis of translational efficiency using anota2seq
Release Lineage
Entered 3.6 · Oct 31, 2017
Current · Requires R 4.6
Description
anota2seq provides analysis of translational efficiency and differential expression analysis for polysome-profiling and ribosome-profiling studies (two or more sample classes) quantified by RNA sequencing or DNA-microarray. Polysome-profiling and ribosome-profiling typically generate data for two RNA sources; translated mRNA and total mRNA. Analysis of differential expression is used to estimate changes within each RNA source (i.e. translated mRNA or total mRNA). Analysis of translational efficiency aims to identify changes in translation efficiency leading to altered protein levels that are independent of total mRNA levels (i.e. changes in translated mRNA that are independent of levels of total mRNA) or buffering, a mechanism regulating translational efficiency so that protein levels remain constant despite fluctuating total mRNA levels (i.e. changes in total mRNA that are independent of levels of translated mRNA). anota2seq applies analysis of partial variance and the random variance model to fulfill these tasks.
None published for Bioconductor
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
35 8 exported
Complexity
15.6 avg / 96 max
Call network
35 nodes / 45 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
7,281
Files
44
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
8
Internal functions
27
Recent export changes
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
0%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
3.4.0
System requirements
–
C++ standard
–
License
GPL-3
License flags
SPDX valid, OSI approved
History
Versions
18
First release
2018-03-19
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
- Help pages
- 19
- Examples that run
- 83%15 run in a plain check · 3 never run
- Exported functions with examples
- 100%
- Documented parameters
- 91%
- Return-value docs
- 100%
- Help pages citing references
- 16%
Repository practices
Checks read the Bioconductor git repository (git.bioconductor.org), branch RELEASE_3_23.
No development-tooling practices detected in the Bioconductor git repository.
Datasets
| Name | Class | Size | Also in |
|---|---|---|---|
| anota2seq_data_P | matrix | 10,748 × 8 | No other package |
| anota2seq_data_T | matrix | 10,748 × 8 | No other package |
| anota2seq_pheno_vec | vector | 8 elements | No other package |
Topics
Depended on by (1)
Bioconductor (1)
People (from the free-text Author field)
Cite
Cite this package
Run in R for the authors' entry:
citation("anota2seq")The package provides a citation file, so citation() returns the authors' own entry.
It points to 10.1093/nar/gkz223.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-23, which the citation names so these numbers can be found later. More on citing and the projects behind them.