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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# pepdiff <a href="https://teammaclean.github.io/pepdiff/"><img src="man/figures/logo.png" align="right" height="138" alt="pepdiff website" /></a>
<!-- badges: start -->
[](https://lifecycle.r-lib.org/articles/stages.html#experimental)
[](https://CRAN.R-project.org/package=pepdiff)
[](https://github.com/TeamMacLean/pepdiff/actions/workflows/R-CMD-check.yaml)
[](https://github.com/TeamMacLean/pepdiff/actions/workflows/pkgdown.yaml)
[](https://opensource.org/licenses/MIT)
[](https://github.com/TeamMacLean/pepdiff/issues)
[](https://github.com/TeamMacLean/pepdiff/stargazers)
<!-- badges: end -->
**Differential abundance analysis for proteomics data.**
pepdiff helps proteomics researchers answer: "What's differentially abundant?"
## Features
- **GLM analysis** -- Gamma GLM with emmeans for factorial designs
- **ART analysis** -- Non-parametric alternative for heavy-tailed data
- **Pairwise tests** -- Wilcoxon, bootstrap-t, Bayes factor, rank products
- **Stratified comparisons** -- Analyse effects within factor levels
- **Fit diagnostics** -- Visual checks for GLM model assumptions
- **Rich visualizations** -- Volcano plots, heatmaps, PCA, p-value histograms
## Installation
Install from GitHub:
```r
# install.packages("pak")
pak::pak("TeamMacLean/pepdiff")
```
## Quick Start
```{r example, eval=FALSE}
library(pepdiff)
# Import data
dat <- read_pepdiff(
"data.csv",
id = "peptide",
gene = "gene_id",
value = "abundance",
factors = c("treatment", "timepoint"),
replicate = "bio_rep"
)
# Run differential analysis
results <- compare(
dat,
compare = "treatment",
ref = "ctrl",
method = "glm"
)
# Visualize results
plot(results)
```
## Documentation
- **[Getting Started](https://teammaclean.github.io/pepdiff/articles/basic_workflow.html)** -- Basic workflow
- **[GLM Analysis](https://teammaclean.github.io/pepdiff/articles/glm_analysis.html)** -- Factorial designs with GLM
- **[ART Analysis](https://teammaclean.github.io/pepdiff/articles/art_analysis.html)** -- Non-parametric alternative
- **[Checking Model Fit](https://teammaclean.github.io/pepdiff/articles/checking_fit.html)** -- Diagnostic plots
- **[Pairwise Tests](https://teammaclean.github.io/pepdiff/articles/pairwise_tests.html)** -- Direct two-group comparisons
- **[Function Reference](https://teammaclean.github.io/pepdiff/reference/index.html)** -- Full API
## Companion Package
**peppwR** answers "How many samples do I need?" (power analysis)
**pepdiff** answers "What's differentially abundant?" (analysis)
See [peppwR](https://github.com/TeamMacLean/peppwR) for experimental design planning.
## Workflow
```mermaid
flowchart LR
A[CSV] --> B[read_pepdiff]
B --> C[pepdiff_data]
C --> D[compare]
D --> E[pepdiff_results]
E --> F[plot]
style A fill:#FFFFCC,stroke:#BD0026
style B fill:#FD8D3C,stroke:#BD0026,color:#fff
style C fill:#FFFFCC,stroke:#BD0026
style D fill:#FD8D3C,stroke:#BD0026,color:#fff
style E fill:#FFFFCC,stroke:#BD0026
style F fill:#FD8D3C,stroke:#BD0026,color:#fff
```
## Citation
If you use pepdiff in your research, please cite:
```
MacLean, D. (2026). pepdiff: Differential Abundance Analysis for
Proteomics Data. R package version 1.0.0.
https://github.com/TeamMacLean/pepdiff
```
## Contributing
Contributions welcome! Please open an [issue](https://github.com/TeamMacLean/pepdiff/issues) or submit a pull request.
## License
MIT