4 papers · 1 filter
Meta-Analysis of High-Dimensional Surrogate Markers
Arthur Hughes, Rodolphe Thiébaut, Layla Parast +1
When direct measurement of a clinically relevant primary endpoint in a clinical trial is infeasible, a surrogate endpoint may be used instead to infer treatment effects. Trial-leve…
Practical limitations for real-life application of data fission and data thinning in post-clustering differential analysis
Benjamin Hivert, Denis Agniel, Rodolphe Thiébaut +1
Post-clustering inference in single-cell RNA sequencing (scRNA-seq) analysis presents significant challenges in controlling Type I error during differential expression analysis. Da…
Scalable Dirichlet Process Mixture Models with Unknown Concentration and Adaptive Covariance for High-Dimensional Clustering Applied to Leukemia Transcriptomics
Annesh Pal, Aguirre Mimoun, Rodolphe Thiébaut +1
We propose a novel method that performs adaptive clustering with DPMM using collapsed VI, while incorporating weakly-informative priors for DP concentration parameter alpha and bas…
RISE: Two-Stage Rank-Based Identification of High-Dimensional Surrogate Markers Applied to Vaccinology
Arthur Hughes, Layla Parast, Rodolphe Thiébaut +1
In vaccine trials with long-term participant follow-up, it is of great importance to identify surrogate markers that accurately infer long-term immune responses. These markers offe…