Seong-Hwan Jun

The paper benchmarks normalization and differential expression methods for miRNA-seq using a realistic dataset, finding RPM normalization and edgeR perform best.

PARiS identifies and removes technical isomiR errors in sRNA-seq data, improving miRNA-level differential expression analysis.

ADTnorm normalizes and integrates CITE-seq datasets to remove batch effects and improve cell-type separation across 13 public datasets.

The paper introduces LNs t-test, a method for differential gene expression analysis in scRNA-seq that reduces bias and improves accuracy compared to existing approaches.

Scuphr reconstructs cell lineage trees using bulk and single-cell DNA sequencing data, addressing technical artifacts and improving accuracy over existing methods.

This study introduces NBSR, a method for differential expression analysis of miRNA-seq data that outperforms existing approaches on simulated and experimental datasets.

PhylEx reconstructs clonal structure by integrating bulk DNA-seq and scRNA-seq data, outperforming existing methods in clonal-tree reconstruction and mutation clustering.