anota
Bioc currentANalysis Of Translational Activity (ANOTA).
Release Lineage
Entered 2.8 · Apr 14, 2011
Current · Requires R 4.6
Description
Genome wide studies of translational control is emerging as a tool to study verious biological conditions. The output from such analysis is both the mRNA level (e.g. cytosolic mRNA level) and the levl of mRNA actively involved in translation (the actively translating mRNA level) for each mRNA. The standard analysis of such data strives towards identifying differential translational between two or more sample classes - i.e. differences in actively translated mRNA levels that are independent of underlying differences in cytosolic mRNA levels. This package allows for such analysis using partial variances and the random variance model. As 10s of thousands of mRNAs are analyzed in parallell the library performs a number of tests to assure that the data set is suitable for such analysis.
Code & tests
Open call graph →Line coverage
–
Expression
–
Tests / Examples
–
Functions
21 4 exported
Complexity
7.8 avg / 46 max
Call network
21 nodes / 24 edges
Test coverage is not measured for Bioconductor packages; nodes fall back to a neutral fill.
Lowest coverage
Per-function coverage is not measured for this package yet.
Code
Structure
Lines of code
2,145
Files
21
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
4
Internal functions
17
Testing & CI
Has tests
No
Test-to-code ratio
0.00
testthat edition
–
CI present
No
CI type
[]
PR gated
No
Docs
Return-value doc rate
100%
\dontrun example ratio
0%
Roxygen coverage
100%
Has pkgdown
No
NEWS present
No
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
–
System requirements
–
C++ standard
–
License
GPL-3
License flags
SPDX valid, OSI approved
History
Versions
31
First release
2011-04-13
Latest release
2026-04-28
Avg cadence
183 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.
Topics
Depended on by (1)
Bioconductor (1)
People
Ola Larsson