We developed scrHLAtag, a novel computational tool for HLA typing at single-cell resolution using long-read sequencing data. This Rust-based pipeline enables researchers to identify and quantify HLA alleles in individual cells from 10X Genomics libraries, providing unprecedented resolution for studying immune cell diversity and T-cell receptor-HLA interactions.
Links HLA alleles to individual cell barcodes and UMIs for precise cellular-level HLA typing
Processes PacBio IsoSeq data for improved HLA allele discrimination up to 3-field nomenclature
We developed single-cell CUT&Tag (scCUT&Tag), a groundbreaking method for profiling chromatin modifications at single-cell resolution. This technique adapts the CUT&Tag approach for use with microfluidic platforms, enabling analysis of chromatin landscapes in individual cells from complex tissues. Published in Nature Biotechnology, this method provides unprecedented insights into epigenetic heterogeneity within cell populations, with applications ranging from developmental biology to cancer research.
Profile chromatin modifications like H3K27me3 in individual cells, revealing heterogeneity masked by bulk approaches
Identify cell types and chromatin state heterogeneity in complex tissues like glioblastoma
Track chromatin dynamics during cellular differentiation from human embryonic stem cells
Monitor polycomb group activity changes in patient samples before and after treatment
Furlan Lab1241 Eastlake Ave E, Seattle, WA
furlan_lab@fredhutch.org