collaborators

7 papers

stat.ME2026

A Joint Bayesian Boolean Matrix Factorization with Application to Chromosomal Copy Number Alterations in Multiple Myeloma

Adolphus Wagala, Samur Mehmet, Giovanni Parmigiani

Boolean matrix factorization provides an interpretable framework for discovering latent binary patterns in high-dimensional data, yet existing methods typically analyze a single bi…

stat.ML2026

A Bayesian Boolean Matrix Factorization with Application to Copy Number Analysis in Cancer

Adolphus Wagala, Mehmet Samur, Giovanni Parmigiani

Binary data factorization is common, but real-valued methods ignore discreteness and yield hard-to-interpret factors. Boolean Matrix Factorization (BooMF) instead decomposes a bina…

stat.ME2026

Poisson process factorization for mutational signature analysis with genomic covariates

Alessandro Zito, Giovanni Parmigiani, Jeffrey W. Miller

Mutational signatures are powerful summaries of the mutational processes altering the DNA of cancer cells. The usual approach to mutational signature analysis consists of decomposi…

stat.ME2026

Multivariate Causal Effects: a Bayesian Causal Regression Factor Model

Dafne Zorzetto, Jenna Landy, Corwin Zigler +2

The impact of wildfire smoke on air quality is a growing concern, contributing to air pollution through a complex mixture of chemical species with important implications for public…

q-bio.QM2025

Bayesian Non-Negative Matrix Factorization with Correlated Mutation Type Probabilities for Mutational Signatures

Iris Lang, Jenna Landy, Giovanni Parmigiani

Somatic mutations, or alterations in DNA of a somatic cell, are key markers of cancer. In recent years, mutational signature analysis has become a prominent field of study within c…

stat.ME2025

Causal Inference for Latent Outcomes Learned with Factor Models

Jenna M. Landy, Dafne Zorzetto, Roberta De Vito +1

In many fields$\unicode{x2013}$including genomics, epidemiology, natural language processing, social and behavioral sciences, and economics$\unicode{x2013}$it is increasingly impor…