Tropism Analysis Package

TAP helps drive discovery of host factors associated with viral tropism in sc/nRNA-seq datasets by automating infectivity clustering, then applying an essemble feature selection pipeline to each subset of cells. The results of each subset are stored and presented in a easy-to-use intuitive interface.

Features

• Explore your data in an interactive user interface.
• Uses an ensemble ML approach to rank important features of tropism.
• Easily share results as an HTML file.
• Simple and configurable parameters.

Installation

We recommend installing in a fresh Python (>=3.12) environment.

pip install scTap

The package is imported in Python as tap:

import tap as t

Live Demo

A curated selection of multiplexed AAV TAPs to explore.
aavdb.com

Usage

TAP accepts an AnnData object or file and generates an interactive HTML report that can be opened in any browser, hosted on a server, or shared. A basic example is shown below. The package expects raw counts in the AnnData object, so the input data should include the original expression values in adata.raw.X for the most reliable results.

import tap as t

parameters = {
    "filename": "PCCM.h5ad",
    "name": "PCCM",
    "genes": ["AAV1", "AAV2", "Retro", "AAV9"],
    "categories": ["cell_type"],
    "outputName": "test.html",
    "excludeMarkers": True,
}

results = t.TAP(**parameters)

The published package name is scTap, but the Python import remains tap.

TAP constructor parameters

The TAP class accepts the following constructor arguments. These options control input data handling, clustering, feature selection, plotting, and output generation.

Commonly used options include genes, categories, outputPath, outputName, excludeMarkers, mapOnly, and runCellTypist.

Citation

Pavan Kenny et al. 2026 Tropism Analysis Package: Interactive Machine Learning Software to Identify Viral Host Factors Through Single-Cell Host-Virus mRNA Profiling. bioRxiv.