Technologies

We are developing novel single cell, high-throughput experimental, computational and machine learning tools aimed at probing the immune system function and dysregulation from unique perspectives.

Published lab and computational methodologies include: 

• scClonetoire - Quantifies intra/inter subset clonality and other repertoire features (2023) (https://github.com/rbr1/scIsoTyper).
• scReptransition - Measures clonal overlap within/between samples (2023) (https://github.com/rbr1/scIsoTyper).
• SVMcelltransfer - Annotates single cells in a scRNA-seq dataset confidently from a reference dataset containing multi-omics (2023) (https://github.com/rbr1/scIsoTyper).
• scIsotyper - Assigns high confidence VDJ chains per droplet (2023) (https://github.com/rbr1/scIsoTyper).
• MLtiplet - scRNA-seq doublet/multiplet detection using multi-omic profiling (2020) (https://github.com/rbr1/MLtiplet_2.0).
• sUMI-seq - Ultrasensitive amplicon barcoding for next-generation sequencing facilitating sequence error and amplification-bias correction (2020) (https://github.com/rbr1/sUMI_processing_pipeline).
• Immune-Repertoire-Network-Generation - open-source program that performs population analyses on B and T cell repertoires (2013) (https://github.com/rbr1/Immune_receptor_NETWORK-GENERATION).