Nicholas E. Navin

Single-Cell Atlas of Renal Cell Carcinoma Brain Metastasis Uncovers Mechanisms of Immune Dysfunction and Resistance

This study uses single-nucleus RNA-seq to analyze RCC brain metastases, identifying immune evasion mechanisms and metabolic adaptations that contribute to resistance to therapy.

A spatial atlas of chemoradiation therapy in pancreatic cancer identifies cellular and microenvironmental determinants of persister populations

This study identifies cellular and microenvironmental factors contributing to radiation therapy resistance in pancreatic cancer using spatial transcriptomics and single-cell RNA sequencing.

cancerSimCraft: A Multi-resolution Cancer Genome Simulator with Comprehensive Ground Truth Tracking

cancerSimCraft simulates cancer genome data at clonal and single-cell resolution, enabling benchmarking of computational methods under varied conditions.

Single cell genome and epigenome co-profiling reveals hardwiring and plasticity in breast cancer

The paper introduces wellDA-seq, a method to co-profile genome and epigenome in single cells, revealing genetic hardwiring and epigenetic plasticity in breast cancer.

A spatially resolved single cell genomic atlas of the adult human breast

This paper constructs a comprehensive spatially resolved single-cell genomic atlas of the adult human breast, identifying 11 major cell types and revealing diverse immune and epithelial cell populations.

Monopogen: single nucleotide variant calling from single cell sequencing

Monopogen calls single nucleotide variants from single-cell sequencing data, achieving high accuracy in germline variant detection and enabling ancestry inference and variant association analysis.

MEDICC2: whole-genome doubling aware copy-number phylogenies for cancer evolution

MEDICC2 infers cancer phylogenies from copy-number data, accounting for whole-genome doubling and parallel evolution, and performs well on simulated and real datasets.

Genomic profiling defines variable clonal relatedness between invasive breast cancer and primary ductal carcinoma in situ

The paper uses genomic profiling to show that some invasive breast cancers are clonally unrelated to their preceding DCIS, suggesting DCIS may act as both a precursor and independent risk factor.

Spatial charting of single cell transcriptomes in tissues

This paper introduces CellTrek, a computational method that integrates scRNA-seq and spatial transcriptomics data to map single cells in tissues, showing accurate spatial organization in mouse and human tissues.

Resolving clonal substructure from single cell genomic data using CopyKit

CopyKit is a computational tool that resolves clonal substructure and reconstructs genetic lineages in tumors using single cell copy number data.

Single-cell copy number lineage tracing enabling gene discovery

The paper introduces MEDALT and LSA to reconstruct copy number lineage trees from single-cell data and identify fitness-associated genes, showing improved accuracy over phylogenetics methods in cancer datasets.

OmicPioneer-sc: an integrated, interactive visualization environment for single-cell sequencing data

OmicPioneer-sc provides an interactive visualization tool for single-cell sequencing data, integrating dimensionality reduction, heat maps, and pathway modules to aid in cell-type annotation and multi-omic analysis.

SiCloneFit: Bayesian inference of population structure, genotype, and phylogeny of tumor clones from single-cell genome sequencing data

SiCloneFit jointly reconstructs tumor clones and their phylogeny from single-cell genome sequencing data using a Bayesian framework to account for technical errors.

SCMarker: ab initio marker selection for single cell transcriptome profiling

SCMarker identifies cell-type-discriminative markers in scRNA-seq data through unsupervised analysis of gene expression patterns without prior knowledge.

SiFit: A Method for Inferring Tumor Trees from Single-Cell Sequencing Data under Finite-site Models

SiFit infers tumor phylogenies from single-cell sequencing data using a finite-sites model, improving accuracy over infinite-sites methods in colorectal cancer datasets.