rnaseqGene
Bioc currentRNA-seq workflow: gene-level exploratory analysis and differential expression
Release Lineage
Entered 3.0 · Oct 14, 2014
Current · Requires R 4.6
Description
Here we walk through an end-to-end gene-level RNA-seq differential expression workflow using Bioconductor packages. We will start from the FASTQ files, show how these were aligned to the reference genome, and prepare a count matrix which tallies the number of RNA-seq reads/fragments within each gene for each sample. We will perform exploratory data analysis (EDA) for quality assessment and to explore the relationship between samples, perform differential gene expression analysis, and visually explore the results.
Call graph
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Code
Structure
Lines of code
2,824
Files
5
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
–
Internal functions
0
Testing & CI
Has tests
No
Test-to-code ratio
–
testthat edition
–
CI present
No
CI type
[]
PR gated
No
Docs
Roxygen coverage
–
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
–
Unsafe pattern score
0
Dep constraint coverage
4.5%
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
24
First release
2014-10-13
Latest release
2026-04-28
Avg cadence
182 days
Cold removal rate
–
Dep drift
32
LOC over versions
Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.
Topics
People
- Michael Love author maintainer
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