seqpac
Bioc currentSeqpac: A Framework for smallRNA analysis in R using Sequence-Based Counts
Release Lineage
Entered 3.17 · Apr 26, 2023
Current · Requires R 4.6
Description
Seqpac provides functions and workflows for analysis of short sequenced reads. It was originally developed for small RNA analysis, but can be implemented on any sequencing raw data (provided as a fastq-file), where the unit of measurement is counts of unique sequences. The core of the seqpac workflow is the generation and subsequence analysis/visualization of a standardized object called PAC. Using an innovative targeting system, Seqpac process, analyze and visualize sample or sequence group differences using the PAC object. A PAC object in its most basic form is a list containing three types of data frames. - Phenotype table (P): Sample names (rows) with associated metadata (columns) e.g. treatment. - Annotation table (A): Unique sequences (rows) with annotation (columns), eg. reference alignments. - Counts table (C): Counts of unique sequences (rows) for each sample (columns). The PAC-object follows the rule: - Row names in P must be identical with column names in C. - Row names in A must be identical with row names in C. Thus P and A describes the columns and rows in C, respectively. The targeting system, will either target specific samples in P (pheno_target) or sequences in A (anno_target) and group them according to a target column in P and A, respectively (see vignettes for more details).
None published for Bioconductor
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
59 40 exported
Complexity
13.8 avg / 129 max
Call network
59 nodes / 57 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
19,856
Files
111
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
47
Internal functions
19
Recent export changes
Testing
Has tests
Yes
Test-to-code ratio
0.00
testthat edition
–
Docs
Roxygen coverage
100%
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
10%
Unsafe pattern score
6
Dep constraint coverage
87.5%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
4.5.0
System requirements
–
C++ standard
–
License
GPL-3
License flags
SPDX valid, OSI approved
History
Versions
7
First release
2023-04-25
Latest release
2026-04-28
Avg cadence
183 days
Cold removal rate
–
Dep drift
1
LOC over versions
Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.
Documentation
- Help pages
- 53
- Examples that run
- 100%53 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 98%
- Return-value docs
- 100%
- Help pages citing references
- 0%
Repository practices
Checks run against github.com/oestlab/seqpac on 2026-10-18.
No development-tooling practices detected in the upstream repository.
Datasets
Topics
People
- Alessandro Gozzo author contributor maintainer
- Anna Asratian author contributor
- Signe Isacson author contributor
- Daniel Natt author funder
- Lovisa Örkenby author contributor
- Anita Öst author funder
Cite
Cite this package
Run in R for the authors' entry:
citation("seqpac")The package provides a citation file, so citation() returns the authors' own entry.
It points to 10.1101/2021.03.19.436151.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-20, which the citation names so these numbers can be found later. More on citing and the projects behind them.