Pawel F. Przytycki

Oct 23, 2024 | nature.com | Michael Alexanian |Tomohiro Nishino |Lin Ye |Clara Lee |Will Flanigan |Zachary Gardner | +7 more

AbstractChronic inflammation and tissue fibrosis are common responses that worsen organ function, yet the molecular mechanisms governing their cross-talk are poorly understood. In diseased organs, stress-induced gene expression changes fuel maladaptive cell state transitions1 and pathological interaction between cellular compartments.

May 17, 2024 | biorxiv.org | Zhirui Hu |Pawel F. Przytycki |Katherine S. Pollard

AbstractCellWalker2 is a graph diffusion-based method for single-cell genomics data integration. It extends the CellWalker model by incorporating hierarchical relationships between cell types, providing estimates of statistical significance, and adding data structures for analyzing multi-omics data so that gene expression and open chromatin can be jointly modeled.

Nov 17, 2023 | biorxiv.org | Pawel F. Przytycki |Katherine S. Pollard |Chan Zuckerberg Biohub

AbstractWhile context-type-specific regulation of genes is largely determined by cis-regulatory regions, attempts to identify cell-type specific eQTLs are complicated by the nested nature of cell types. We present a network-based model for hierarchical annotation of bulk-derived eQTLs to levels of a cell type tree using single cell chromatin accessibility data and no clustering of cells into discrete cell types.

Nov 17, 2023 | biorxiv.org | Pawel F. Przytycki |Katherine S. Pollard |Chan Zuckerberg Biohub

AbstractWhile context-type-specific regulation of genes is largely determined by cis-regulatory regions, attempts to identify cell-type specific eQTLs are complicated by the nested nature of cell types. We present a network-based model for hierarchical annotation of bulk-derived eQTLs to levels of a cell type tree using single cell chromatin accessibility data and no clustering of cells into discrete cell types.

Jul 25, 2023 | nature.com | Pawel F. Przytycki

A hierarchical Bayesian method identifies cell-type specific changes in gene regulatory circuits in disease by integrating single-cell and three-dimensional measurements of the genome. With the advent of single-cell sequencing technology, it is now possible to take measurements of gene expression (scRNA-seq) and chromatin accessibility (scATAC-seq) in individual cells5.