Plaid (Pathway Level Average Intensity Detection) is an ultra-fast method to compute single-sample enrichment scores for gene expression or proteomics data. For each sample, plaid computes the gene set score as the average intensity of the genes/proteins in the gene set. The output is a gene set score matrix suitable for further analyses.
Plaid is freely available on GitHub. It's a main gene sets scoring algorithm in OmicsPlayground, our Bioinformatics platform at BigOmics Analytics. In OmicsPlayground, you can perform Plaid without coding needs.
You can install plaid from Bioconductor:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("plaid")You can also install the development version from GitHub:
if (!require("remotes", quietly = TRUE))
install.packages("remotes")
remotes::install_github("bigomics/plaid")For detailed usage examples and tutorials, please see our vignettes:
Key features:
- Ultra-fast single-sample gene set enrichment scoring
- Automatically detects and handles Bioconductor objects (
SummarizedExperiment,SingleCellExperiment,BiocSet) - Works with regular matrices, sparse matrices, and Bioconductor data structures
- Includes multiple scoring methods (plaid, sing, ssgsea, scSE, ucell, gsva)
- Built-in differential enrichment testing
For support feel free to reach our Bioinformatics Data Science Team at BigOmics Analytics: help@bigomics.ch