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sequencing

Bioc current

Introduction to Bioconductor for Sequence Data

v1.36.0 · Package record · workflows · Artistic-2.0

Release Lineage

Entered 2.12 · Apr 4, 2013

Current · Requires R 4.6

1.0 In 27 of 49 releases 3.23

Description

Bioconductor enables the analysis and comprehension of high- throughput genomic data. We have a vast number of packages that allow rigorous statistical analysis of large data while keeping technological artifacts in mind. Bioconductor helps users place their analytic results into biological context, with rich opportunities for visualization. Reproducibility is an important goal in Bioconductor analyses. Different types of analysis can be carried out using Bioconductor, for example; Sequencing : RNASeq, ChIPSeq, variants, copy number etc.; Microarrays: expression, SNP, etc.; Domain specific analysis : Flow cytometry, Proteomics etc. For these analyses, one typically imports and works with diverse sequence-related file types, including fasta, fastq, BAM, gtf, bed, and wig files, among others. Bioconductor packages support import, common and advanced sequence manipulation operations such as trimming, transformation, and alignment including quality assessment.

Advisories

None published for Bioconductor

Code intelligence has not been computed for this package yet.

Code

Structure

Lines of code

354

Files

3

Compiled share

0%

Has compiled src

No

Language breakdown

Vignettes 354 (100%)

API

Exported functions

–

Internal functions

0

Testing

Has tests

No

Test-to-code ratio

–

testthat edition

–

Docs

Roxygen coverage

–

Health & Security signals

Informational signals; not verdicts.

on.exit coverage

–

Unsafe pattern score

0

Dep constraint coverage

0%

Secret pattern count

0

Bundled 3rd-party code

2 items

Portability & License

Min R version

3.3.0

System requirements

–

C++ standard

–

License

Artistic-2.0

License flags

SPDX valid, OSI approved

History

Versions

27

First release

2013-07-29

Latest release

2026-04-28

Avg cadence

182 days

Cold removal rate

–

Dep drift

11

LOC over versions

v3.6: 358 LOCv3.7: 371 LOCv3.8: 371 LOCv3.9: 354 LOCv3.10: 354 LOCv3.11: 354 LOCv3.12: 354 LOCv3.13: 354 LOCv3.14: 354 LOCv3.15: 354 LOCv3.16: 354 LOCv3.17: 354 LOCv3.18: 354 LOCv3.19: 354 LOCv3.20: 354 LOCv3.21: 354 LOCv3.22: 354 LOCv3.23: 354 LOC

Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.

Documentation

In the Bioconductor 3.23 release
READMENoVignettesYes · 1 · dynamicNEWSNoCitation fileNoWebsiteYes
Help pages
No help pages
Examples that run
no examples
Exported functions with examples
not tracked
Documented parameters
not tracked
Return-value docs
not tracked
Help pages citing references
not tracked

Repository practices

Bioconductor git repository

Checks read the Bioconductor git repository (git.bioconductor.org), branch RELEASE_3_23.

No development-tooling practices detected in the Bioconductor git repository.

Topics

Available on

CRANr2uBioconductorautoCRANCOPR

People

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("sequencing")
Bioconductor Package Maintainer, Arora, S., & Morgan, M. (2026). sequencing: Introduction to Bioconductor for Sequence Data (Version 1.36.0) [Computer software]. https://bioconductor.org/packages/sequencing

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for sequencing version 1.36.0 [Data set]. HJJB, LLC. Data release v2026-10-19. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-19, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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