Robert B. Scharpf

mFrag improves lung cancer early detection using fragmentomics by integrating DNA methylation data and combining two models to enhance prediction accuracy.

This study tracks ctDNA and immune cell changes in lung cancer patients on immunotherapy to identify molecular responses and immune-related toxicities.

The paper evaluates edgeR for PhIP-Seq data analysis and introduces BEER, a Bayesian framework for improved normalization and analysis.

This paper introduces PICTograph, a Bayesian model for estimating cancer cell fractions and clone trees from multi-region sequencing data, showing improved accuracy in subclone reconstruction and evolutionary inference.

This paper develops a Bayesian method to detect copy number variants and assess their association with disease in large-scale studies, finding deletions near MYC and TUSC3 linked to pancreatic cancer.

The paper develops MDTS, a method for detecting de novo copy number deletions in parent-offspring trios from targeted sequencing, achieving higher precision and scalability than existing tools.