Shian Su

LongBench benchmarks long-read RNA-sequencing technologies using a cross-platform dataset of cancer cell lines, showing high gene-level concordance but reduced transcript-level consistency across platforms.

This paper develops D4Z4End2End, a workflow using long-read sequencing to characterize D4Z4 macrosatellite genetics and methylation in FSHD, BAMS, and reference cohorts, revealing new variants and methylation patterns.

stPipe provides a flexible R/Bioconductor pipeline for preprocessing spatial transcriptomics data from multiple platforms, enabling standardized analysis and benchmarking.

This study uses adaptive nanopore sequencing to measure X inactivation skew in carrier females with X-linked retinal diseases, showing a strong correlation between skew and disease presentation.

scPipe provides a preprocessing pipeline for single-cell ATAC-Seq and multi-modal data in R/Bioconductor, enabling quality control and downstream analysis.

The paper develops FLT-seq and FLAMES to characterize full-length isoforms in single cells of human and mouse, identifying thousands of unannotated isoforms and linking them to functional modules and drug resistance mutations.

Glimma 2.0 enhances interactive RNA-seq analysis with reproducible R Markdown integration and improved visualization tools.

This study benchmarks 9 scRNA-seq preprocessing workflows, finding that while they vary in gene detection and quantification, downstream analysis with effective normalization and clustering methods leads to consistent clustering results.

This study analyzes nanopore long-read RNA-seq data using short-read tools to assess differential gene and isoform expression in synthetic and mouse datasets.

NanoMethViz provides an R/Bioconductor package for visualizing long-read methylation data, offering tools to explore methylation patterns at multiple resolutions.

The paper demonstrates that intron reads from RNA-seq are informative and introduces methods to analyze them for transcriptional changes and intron retention.

BiocPkgTools provides a toolkit to access and analyze metadata from the Bioconductor package ecosystem, enabling downstream applications like data mining and graph analytics.

The paper benchmarks scRNA-seq analysis methods using synthetic datasets generated from mixed cancer cell lines, identifying methods that perform well across tasks like normalization, clustering, and integration.

SIS-seq links gene expression with cell fate by analyzing clonal progeny, identifying early gene signatures of dendritic cell subset development.

scPipe provides a flexible R/Bioconductor pipeline for preprocessing scRNA-seq data, handling multiple barcoding strategies and generating quality reports for downstream analysis.

Glimma provides interactive graphics for gene expression analysis to enhance data exploration and sharing between bioinformaticians and biologists.