Area of research
Molecular Biology · Cancer Research
Research interest
Research interests include Single-cell and spatial transcriptomics, Cancer Genomics and Diagnostics, Cell Image Analysis Techniques, and RNA Research and Splicing.
Demuxafy: improvement in droplet assignment by integrating multiple single-cell demultiplexing and doublet detection methods
Optimizing expression quantitative trait locus mapping workflows for single-cell studies
Optimising expression quantitative trait locus mapping workflows for single-cell studies
Eleven grand challenges in single-cell data science
Benchmarking single-cell RNA-sequencing protocols for cell atlas projects
Single-cell RNA-sequencing of differentiating iPS cells reveals dynamic genetic effects on gene expression
Properties of structural variants and short tandem repeats associated with gene expression and complex traits
Cardelino: computational integration of somatic clonal substructure and single-cell transcriptomes
Discovery and quality analysis of a comprehensive set of structural variants and short tandem repeats
Publisher Correction: Single-cell RNA-sequencing of differentiating iPS cells reveals dynamic genetic effects on gene expression
Combined single-cell profiling of expression and DNA methylation reveals splicing regulation and heterogeneity
Single-cell RNA-sequencing of differentiating iPS cells reveals dynamic genetic effects on gene expression
12 Grand Challenges in Single-Cell Data Science
Vireo: Bayesian demultiplexing of pooled single-cell RNA-seq data without genotype reference
12 Grand challenges in single-cell data science
12 Grand challenges in single-cell data science
12 Grand Challenges in Single-Cell Data Science
Visualization of Biomedical Data
Cardelino: Integrating whole exomes and single-cell transcriptomes to reveal phenotypic impact of somatic variants
Visualization of Biomedical Data
Common genetic variation drives molecular heterogeneity in human iPSCs
f-scLVM: scalable and versatile factor analysis for single-cell RNA-seq
NOX1 loss-of-function genetic variants in patients with inflammatory bowel disease
Sequence data and association statistics from 12,940 type 2 diabetes cases and controls
Scater: pre-processing, quality control, normalization and visualization of single-cell RNA-seq data in R
A step-by-step workflow for low-level analysis of single-cell RNA-seq data with Bioconductor
The genetic architecture of type 2 diabetes
A step-by-step workflow for low-level analysis of single-cell RNA-seq data
Factors influencing success of clinical genome sequencing across a broad spectrum of disorders
Count-based differential expression analysis of RNA sequencing data using R and Bioconductor