CiteFuse

CiteFuse integrates RNA and antibody-derived tag (ADT) measurements from CITE-seq to enable joint analysis of gene transcription and cell-surface protein expression at single-cell resolution.

Key Features:

• Pre-processing: Handling of raw CITE-seq counts and ADT data to prepare inputs for downstream analysis.
• Modality Integration: Integration of RNA and antibody-derived tag (ADT) data to generate combined molecular profiles.
• Clustering: Algorithms for identifying cell populations from integrated RNA and ADT profiles.
• Differential Expression Analysis: Tests to detect differential expression at both RNA and protein (ADT) levels.
• ADT Evaluation: Assessment of antibody-derived tag quality and signal to ensure reliable protein measurement.
• Ligand-Receptor Interaction Analysis: Prediction of ligand–receptor interactions using integrated multi-modal data.
• Doublet Detection: Detection of doublets by combining cell hashing information with transcriptome profiles.

Scientific Applications:

• Multi-modal CITE-seq analysis: Joint analysis of RNA transcripts and cell-surface proteins in CITE-seq datasets.
• Cell population identification: Improved cell-type and population discovery using combined RNA and ADT signals.
• Ligand–receptor inference: Inference of intercellular ligand–receptor interactions from integrated multi-modal data.
• Benchmarking and quality control: Evaluation on simulated and real-world CITE-seq datasets, demonstrating advantages over single-modality profiling and enabling doublet detection.

Methodology:

Pre-processing of raw CITE-seq and ADT counts, integration of RNA and ADT modalities, clustering, differential expression analysis at RNA and protein levels, ADT quality assessment, ligand–receptor interaction prediction, and doublet detection combining cell hashing with transcriptome data.