Sydney M. Shaffer

SupeRJump identifies differentiation fate and discontinuous transitions in leukemia using a semi-supervised jump diffusion model applied to scRNA-seq data.

CloneSweeper enables multiplexed lineage tracking to identify pre-existing resistant lineages in melanoma, revealing a primed state associated with de-differentiation and inflammatory signaling.

This study finds BRCA1 and BRCA2 carriers have increased DNA damage and growth in gastric epithelium and organoids, suggesting haploinsufficiency contributes to early gastric cancer development.

Clonotrace integrates gene expression and clonotype data to infer cell state transitions and fate biases, improving understanding of lineage dynamics in various biological systems.

SUMMIT traces mitochondrial mutations in human tissues to identify spatially localized clones and their transcriptomic profiles.

The paper shows that H3K36M oncohistone inhibits NSD2, leading to SETD2-dependent antiviral immune response and tumor clearance in KRAS-driven lung cancer.

This study identifies FOXM1 as a key driver of epithelial disruption in EoE, showing that its inhibition restores differentiation, reduces hyperplasia, and improves barrier function.

The paper identifies ERBB2 alterations as a recurrent oncogene in esophageal adenocarcinoma brain metastases and links them to monoclonal seeding and treatment response.

SpaceBar enables clone tracing and spatial transcriptomics profiling by using synthetic barcodes to label cells and analyze gene expression in situ.

This study compares chemotherapy with and without stroma-directed drugs in a mouse model of pancreatic cancer, finding enhanced tumor growth inhibition and changes in tumor microenvironment.

The paper identifies non-genetic factors influencing proliferation variability in esophageal epithelial clones using clonal tracing and scRNA-seq.

This study tracks resistant cancer clones through treatment using single-cell RNA-sequencing and barcoding, showing clones have distinct fates and gene expression states that predict survival.

The paper develops a method to quantify gene expression memory and identify regulators of cell state transitions, showing that modulating PI3K and TGF-β pathways can reduce drug resistance in melanoma.

The paper identifies clonal cell states in Barrett's esophagus and links them to esophageal adenocarcinoma progression through single-cell lineage tracing and transcriptional profiling.

The paper introduces MemorySeq, a method to identify gene expression fluctuations persisting across cell divisions, revealing non-genetic, heritable cellular behaviors in cancer cell lines.

The paper identifies rare cell states in melanoma that contribute to drug resistance by analyzing single-cell gene expression and signaling dynamics.

TooManyCells identifies and visualizes cell clades using graph-based tools, outperforming existing methods in detecting rare populations in single-cell RNA-seq data.

The paper introduces DESCEND, a method to deconvolve true gene expression distributions from noisy scRNA-seq data, improving estimates of dispersion and burstiness while adjusting for covariates.

SAVER improves gene expression estimates in scRNA-seq by imputing zeros and enhancing low/moderate expression genes, improving downstream analysis accuracy.

This paper compares single cell RNA sequencing and single molecule RNA FISH for rare cell analysis, finding that higher transcriptome complexity per cell improves accuracy for small gene sets.