Malcolm C. Moos

A benchmarking study of copy number variation inference methods using single-cell RNA-sequencing data

This study benchmarks five scCNV inference methods across multiple scRNA-seq platforms and mixed samples, finding variations in performance based on data characteristics and batch effects.

Epigenomic, transcriptomic and proteomic characterizations of reference samples

The paper provides comprehensive reference materials with genomic, epigenomic, transcriptomic, scRNA-seq, and proteomic characterizations of two cell lines for benchmarking and validation.

Establishing reference samples for detection of somatic mutations and germline variants with NGS technologies

The paper establishes reference samples with high-coverage whole-genome sequencing to create truth sets for somatic mutation and germline variant detection using NGS technologies.

Achieving reproducibility and accuracy in cancer mutation detection with whole-genome and whole-exome sequencing

This study evaluates reproducibility and accuracy of cancer mutation detection using whole-genome and whole-exome sequencing across multiple sequencing centers and bioinformatics pipelines.

A Multi-center Cross-platform Single-cell RNA Sequencing Reference Dataset

The paper presents a multi-center cross-platform scRNA-seq reference dataset for benchmarking bioinformatics methods across different platforms and centers.

A Comprehensive Multi-Center Cross-platform Benchmarking Study of Single-cell RNA Sequencing Using Reference Samples

This study benchmarks scRNA-seq reproducibility across platforms and pipelines, finding that batch correction methods significantly affect results.