BOOTSTRAP2

Two-level hierarchical bootstrap for single-cell differential expression.

Installation

Python 3.10 or newer is required. Install with:

python -m pip install bootstrap2-sc

For installation from a local source checkout:

python -m pip install .

Input

Provide an AnnData object containing raw counts in adata.X.

Each subject must belong to one condition and one batch. The method supports the nested batch--subject design, not general covariate adjustment, paired/repeated subjects or condition-batch confounding.

Python API

import anndata as ad
from bootstrap2 import bootstrap2h

adata = ad.read_h5ad("counts.h5ad")
result = bootstrap2h(
    adata,
    condition=("SLE", "Control"),
    n_bootstraps=10000,
    n_jobs=4,
    seed=0,
    lfc=0.0,
)
result.to_csv("results.tsv", sep="\t")

The input AnnData is not modified. Use layer="counts" to select a raw-count layer in the API.

With condition=("SLE", "Control"), a positive LFC indicates higher expression in SLE. Use condition_col, sample_col and batch_col for alternative metadata field names.

Output

Returns a DataFrame indexed by gene, with p_val and lfc columns.