LINGER (LIfelong neural Network for GEne Regulation) is a novel method to infer GRNs from single-cell multiome data built on top of PyTorch.
LINGER incorporates both 1) atlas-scale external bulk data across diverse cellular contexts and 2) the knowledge of transcription factor (TF) motif matching to cis-regulatory elements as a manifold regularization to address the challenge of limited data and extensive parameter space in GRN inference.
In the user guide, we provide an overview of each task.
LINGER can be installed by pip
conda create -n LINGER python==3.10.0
conda activate LINGER
pip install LingerGRN==1.67
conda install bioconda::bedtools # Requirment
We provide several tutorials and user guide. If you find our tool useful for your research, please consider citing the LINGER manuscript.
User guide | PBMCs tutorial | H1 cell line tutorial |
GRN benchmark | In silico perturbation | Other species |
If you use LINGER, please cite: