DspikeIn
Bioc currentEstimating Absolute Abundance from Microbial Spike-in Controls
Release Lineage
Entered 3.22 · Oct 30, 2025
Current · Requires R 4.6
Description
Provides a reproducible and modular workflow for absolute microbial quantification using spike-in controls. Supports both single spike-in taxa and synthetic microbial communities with user-defined spike-in volumes and genome copy numbers. Compatible with 'phyloseq' and 'TreeSummarizedExperiment' (TSE) data structures. The package implements methods for spike-in validation, preprocessing, scaling factor estimation, absolute abundance conversion, bias correction, and normalization. Facilitates downstream statistical analyses with 'DESeq2', 'edgeR', and other Bioconductor-compatible methods. Visualization tools are provided via 'ggplot2', 'ggtree', and related packages. Includes detailed vignettes, case studies, and function-level documentation to guide users through experimental design, quantification, and interpretation.
None published for Bioconductor
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
76 63 exported
Complexity
7.1 avg / 30 max
Call network
76 nodes / 90 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
14,707
Files
171
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
61
Internal functions
13
Recent export changes
Testing
Has tests
Yes
Test-to-code ratio
0.08
testthat edition
–
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
4.1.0
System requirements
–
C++ standard
–
License
MIT + file LICENSE
License flags
SPDX valid, OSI approved
History
Versions
2
First release
2025-10-29
Latest release
2026-04-28
Avg cadence
181 days
Cold removal rate
–
Dep drift
0
LOC over versions
Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.
Documentation
- Help pages
- 79 (1 internal)
- Examples that run
- 93%55 run in a plain check (42 of them under a condition) · 1 only when donttest examples are enabled (R CMD check --as-cran) · 3 never run
- Exported functions with examples
- 88%
- Documented parameters
- 99%
- Return-value docs
- 100%
- Help pages citing references
- 0%
- DspikeIn with TSE HTML
Repository practices
1 development-tooling and community-health practice detected across 1 family in the upstream repository
Checks run against github.com/mghotbi/dspikein on 2026-10-11.
GitHub Pages site last deployed 2025-10-05
Datasets
| Name | Class | Size | Also in |
|---|---|---|---|
| AcceptableRange | data.frame | 113,631 × 10 | No other package |
| metadata_full | data.frame | 312 × 46 | No other package |
| physeq | – | – | – |
| physeq_16SOTU | – | – | – |
| physeq_ITSOTU | – | – | – |
| tse | – | – | – |
Topics
People
- Mitra Ghotbi author maintainer
- Marjan Ghotbi contributor
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("DspikeIn")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.
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.