Boris P. Hejblum

cit_gsa is a single-cell RNA-seq gene set analysis method that allows covariate adjustment and handles multiple conditions, showing improved performance in complex scenarios.

The paper evaluates deconvolution methods' robustness to incomplete reference matrices and introduces DICEPro to improve performance by adjusting reference signatures.

The paper identifies an issue in RNA-seq data simulation where normalization neglect leads to false positives and provides corrected results showing dearseq's performance.

This paper adapts the Generalized Berk-Jones statistic for time-to-event outcomes in gene set analysis, comparing it to other methods in gliomas and breast cancer.

This paper introduces a distribution-free method for scRNA-seq differential expression analysis that handles complex hypotheses and multiple conditions, showing good performance in simulations and a real dataset.

dearseq is a differential expression analysis method that controls the false discovery rate without assuming data distribution, showing improved performance over existing methods in simulations and real data.

cytometree is an automated flow cytometry gating algorithm that outperforms existing methods in accuracy and speed.