Hanlee P. Ji

This study identifies a unique aneuploidy profile in colorectal cancer brain metastases compared to other cancer types and metastatic sites.

The paper identifies progranulin as a mediator of immune suppressive niches in brain metastasis using cross-species spatial transcriptomics and functional analyses.

The paper identifies OLFM4 as a marker of high-risk gastric intestinal metaplasia, showing its restricted localization to epithelial glands and focal expansion with disease severity.

This study identifies the immunosuppressive cellular and genomic features of colorectal cancer brain metastases and their mechanisms of adaptation.

Clonalscope detects cancer subclones using DNA copy number data from single-cell and spatial omic sequencing, identifying spatially segregated subclones and validating them with matched scDNA-seq data.

This study analyzes DNA fragmentation and methylation in CSF-derived cfDNA from NSCLC-BMET patients and finds distinct patterns compared to controls and plasma-derived cfDNA.

The paper introduces CLONEID, a framework for organizing clone-resolved data to enable longitudinal genotype-to-phenotype mapping in experiments with repeated molecular and phenotypic measurements.

This study uses spatial single-cell analysis to identify 10 cell phenotypes in stage III colorectal cancers and links specific spatial features to recurrence risk.

The paper identifies a 26-gene expression signature in high-risk gastric intestinal metaplasia (GIM) that localizes to intestinal stem-like cells and is associated with increased gastric cancer risk.

KmerSV visualizes and annotates structural variants using k-mers and the Human Pangenome reference.

This paper introduces MDRAM, a DNA-based random access memory system that enables efficient and scalable readouts using nanopore sequencing and magnetic bead conjugation.

The paper introduces Minigraph-Cactus, a pangenome pipeline that constructs pangenome graphs directly from whole-genome alignments, demonstrating improved performance in mapping and variant calling across human and Drosophila data.

The paper presents a draft human pangenome reference that improves variant discovery and structural variant detection compared to existing references.

The paper shows recombination between heterologous human acrocentric chromosomes using pangenome data, revealing pseudo-homologous regions linked to Robertsonian translocations.

The paper develops a nanopore sequencing strategy to measure cfDNA methylomes in cancer patients, enabling longitudinal monitoring during treatment.

The paper develops Longcell, a statistical framework for accurate isoform quantification in single cell and spatial long-read sequencing data, revealing intra-cell splicing heterogeneity and validating regulatory targets.

The paper develops a method to detect complex structural variants across human genomes and finds they are associated with phenotypic hotspots and evolutionary changes.

The paper introduces niche-differential expression analysis to identify context-dependent cell-cell interactions in spatial transcriptomics data and applies it to colorectal cancer metastases.

This study develops a single-cell method using nanopore sequencing to identify somatic mutations and gene rearrangements in cancer cells and integrates these with transcriptomes.

The paper develops a single-cell CRISPR base editor method to engineer and assess the transcriptional impact of cancer mutations in cell lines.

The paper analyzes the Human Pangenome to identify conserved and polymorphic structural variations across diverse haploid assemblies.

The paper integrates scDNA-seq and scRNA-seq data to characterize subclonal architecture and pathway activity in gastric and colorectal cancers.

The paper describes the development of a gastric cancer registry integrating clinical and genomic data to support translational research.

KmerKeys provides a web tool for efficient k-mer-based querying of genome assemblies and variant databases.

This paper introduces HEMnet, a deep learning model that transfers molecular labels from immunohistochemistry to H&E images to identify cancer cells without manual annotation.

The paper develops a single-cell method combining CRISPR edits and long-read sequencing to characterize transcript isoforms and confirm genomic edits at single-cell resolution.

This study identifies a consensus microbiome for colorectal cancer by analyzing 924 tumors across eight RNA-Seq datasets, finding 114 microbial species consistently associated with tumors.

The paper develops a high-coverage sequencing approach to profile microsatellite and chromosomal instability in colorectal cancer, revealing co-occurrence of MSI and CIN features.

Alleloscope analyzes allele-specific copy number and chromatin accessibility in single-cell cancer data, revealing complex copy number events and their role in intratumor heterogeneity.

The paper develops a method using k-mer sequences to validate somatic mutations in cancer genome sequencing data, showing it effectively identifies true positive mutations including insertions and deletions.