lncRna
Bioc currentA Comprehensive Workflow for Long Non-coding RNA Identification and Functional Analysis
Release Lineage
Entered 3.23 · Apr 29, 2026
Current · Requires R 4.6
Description
Provides a complete workflow for the identification, analysis, and functional annotation of long non-coding RNAs (lncRNAs) from RNA-Seq data. The package includes functions for filtering transcripts from GTF files, evaluating the performance of multiple coding potential prediction tools (e.g., CPC2, PLEK, CPAT), and summarizing their agreement. It enables systematic performance analysis of individual tools, "at least N" tool consensus, and all possible tool combinations. Functional analysis is supported through the identification of potential cis- and trans-acting interactions with protein-coding genes, followed by enrichment analysis. Results can be visualized using a variety of plots, including radar plots, clock plots, and interactive Sankey diagrams.
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
44 18 exported
Complexity
5 avg / 22 max
Call network
44 nodes / 30 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
4,665
Files
61
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
18
Internal functions
26
Recent export changes
Testing & CI
Has tests
Yes
Test-to-code ratio
0.20
testthat edition
3
CI present
No
CI type
[]
PR gated
No
Docs
Roxygen coverage
100%
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
100%
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
MIT + file LICENSE
License flags
SPDX valid, OSI approved
History
Versions
1
First release
2026-04-28
Latest release
2026-04-28
Avg cadence
–
Cold removal rate
–
Dep drift
0
Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.
Documentation
- Examples that run
- 100%
- Documented parameters
- 98%
- Return-value docs
- 100%
- References docs
- 0%
Topics
People
- Jan Pawel Jastrzebski author maintainer
- Wiktor Babis contributor
- Damian Czopek contributor author
- Monika Gawronska contributor
- Hugo Gruson contributor
- Mariusz Jankowski contributor
- Stefano Pascarella contributor