Katie Marie Campbell

CytoRipple identifies tissue-level polarization vector fields from spatial multi-omic data to reveal multi-cellular structures and their functional associations.

SpaceBender denoises spatial transcriptomics data by leveraging spatial information, improving biological signal clarity and statistical significance in simulations and real tissues.

This paper introduces TopKAT, a topology-based method to detect associations between spatial cell structures and clinical outcomes in spatial proteomics data.

The paper introduces SPOT, a method to assess spatial clustering in proteomic data across multiple radii, and demonstrates its application in ovarian cancer.

RegTools identifies splice-associated variants in cancer by integrating genomic and transcriptomic data across 9,000 tumor samples, discovering 235,778 splicing events.

The paper describes the evolution of the CIViC knowledgebase to meet the needs of the cancer variant interpretation community by expanding its functionality and data types.

The paper evaluates nucleic acid extraction kits and RNA sequencing library preparations for FFPE clinical samples, finding that combinations of methods affect transcriptome analysis.

The paper designs single molecule molecular inversion probes targeting clinically relevant variants using the CIViC database, demonstrating high sensitivity and discovering missed variants in cancer samples.

This paper establishes a standard operating procedure for manual refinement of somatic variants in tumor sequencing data to improve consistency and reproducibility.

The paper identifies somatic mutations with prognostic effects in ER+ breast cancer using genomic data from multiple cohorts.