DaMiRseq
Bioc currentData Mining for RNA-seq data: normalization, feature selection and classification
Release Lineage
Entered 3.5 · Apr 25, 2017
Current · Requires R 4.6
Description
The DaMiRseq package offers a tidy pipeline of data mining procedures to identify transcriptional biomarkers and exploit them for both binary and multi-class classification purposes. The package accepts any kind of data presented as a table of raw counts and allows including both continous and factorial variables that occur with the experimental setting. A series of functions enable the user to clean up the data by filtering genomic features and samples, to adjust data by identifying and removing the unwanted source of variation (i.e. batches and confounding factors) and to select the best predictors for modeling. Finally, a "stacking" ensemble learning technique is applied to build a robust classification model. Every step includes a checkpoint that the user may exploit to assess the effects of data management by looking at diagnostic plots, such as clustering and heatmaps, RLE boxplots, MDS or correlation plot.
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
24 24 exported
Complexity
23.6 avg / 56 max
Call network
24 nodes / 2 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
8,473
Files
85
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
24
Internal functions
0
Recent export changes
Testing & CI
Has tests
Yes
Test-to-code ratio
0.08
testthat edition
–
CI present
No
CI type
[]
PR gated
No
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
System requirements
–
C++ standard
–
License
GPL (>= 2)
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
100%
Dep drift
7
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
- 21%
Topics
Depended on by (1)
Bioconductor (1)
People
Mattia Chiesa
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("DaMiRseq")Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-08-18, which the citation names so these numbers can be found later. More on citing and the projects behind them.