ISAnalytics
Bioc currentAnalyze gene therapy vector insertion sites data identified from genomics next generation sequencing reads for clonal tracking studies
Release Lineage
Entered 3.12 · Oct 28, 2020
Current · Requires R 4.6
Description
In gene therapy, stem cells are modified using viral vectors to deliver the therapeutic transgene and replace functional properties since the genetic modification is stable and inherited in all cell progeny. The retrieval and mapping of the sequences flanking the virus-host DNA junctions allows the identification of insertion sites (IS), essential for monitoring the evolution of genetically modified cells in vivo. A comprehensive toolkit for the analysis of IS is required to foster clonal trackign studies and supporting the assessment of safety and long term efficacy in vivo. This package is aimed at (1) supporting automation of IS workflow, (2) performing base and advance analysis for IS tracking (clonal abundance, clonal expansions and statistics for insertional mutagenesis, etc.), (3) providing basic biology insights of transduced stem cells in vivo.
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
284 83 exported
Complexity
4.2 avg / 34 max
Call network
284 nodes / 468 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
33,456
Files
172
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
83
Internal functions
201
Testing & CI
Has tests
Yes
Test-to-code ratio
0.52
testthat edition
3
CI present
Yes
CI type
["github-actions"]
PR gated
Yes
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
4.5
System requirements
–
C++ standard
–
License
CC BY 4.0
License flags
SPDX valid, not OSI
History
Versions
12
First release
2021-04-08
Latest release
2026-04-28
Avg cadence
131 days
Cold removal rate
100%
Dep drift
22
LOC over versions
Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.
Documentation
- Examples that run
- 94%
- Documented parameters
- 92%
- Return-value docs
- 100%
- References docs
- 0%
Datasets
| Name | Class | Rows × Cols | Also in |
|---|---|---|---|
| association_file | data.table | 53 × 83 | No other package |
| integration_matrices | data.table | 1,689 × 8 | No other package |
| proto_oncogenes | tibble | 569 × 13 | No other package |
| refGenes_hg19 | tibble | 27,275 × 12 | No other package |
| refGenes_hg38 | tibble | 84,888 × 12 | No other package |
| refGenes_mm10 | tibble | 55,316 × 12 | No other package |
| refGenes_mm9 | tibble | 24,487 × 12 | No other package |
| tumor_suppressors | tibble | 523 × 13 | No other package |
Topics
People
- Francesco Gazzo maintainer
- Andrea Calabria author
- Giulia Pais author
- Giulio Spinozzi author
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("ISAnalytics")This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-08-26, which the citation names so these numbers can be found later. More on citing and the projects behind them.