TCRfoundation Documentation¶
A multimodal foundation model for single-cell immune profiling
TCRfoundation integrates gene expression and TCR sequences (α and β chains) from paired single-cell measurements through self-supervised pretraining with masked reconstruction and cross-modal contrastive learning.
Features¶
Multimodal Learning: Integrates TCR sequences and gene expression
Multiple Tasks: Classification, regression, and cross-modal prediction
Pretrained Models: Ready-to-use foundation model
Rich Analysis: Built-in evaluation and visualization tools
Quick Start¶
Installation:
pip install tcrfoundation
Basic usage:
import tcrfoundation as tcrf
import scanpy as sc
# Load pretrained model
model = tcrf.load_foundation_model("path/to/checkpoint.pt")
# Fine-tune for classification
results, adata = tcrf.finetune.classification.train_classifier(
adata,
label_column="cell_type",
checkpoint_path="path/to/checkpoint.pt"
)
Contents¶
Getting Started
Tutorials