Bahman Afsari

This study establishes patient-derived KS xenografts that maintain KSHV infection and recapitulate KS tumor gene signatures, enabling analysis of tumor microenvironment cell communications.

Hobotnica estimates molecular signature quality by assessing their ability to stratify data and assign significance scores for comparing different groups.

This paper introduces EVAsc, a method to analyze expression variation in scRNA-seq data to quantify tumor heterogeneity across cell types, subtypes, and patients.

The paper introduces REVA, a nonparametric correlation measure for multivariate data, showing it is robust to noise, high dimensions, and outliers, and applies it to cancer biology.

SEVA identifies differential heterogeneity in gene isoform usage between cancer subtypes using RNA-seq data.