Yupei You

FLAMESv2 is a flexible R/Bioconductor package for analyzing long-read single-cell RNA-seq data, demonstrating field-leading performance in isoform analysis and cell-type identification.

The paper uses long-read sequencing to identify novel RNA isoforms in neuropsychiatric risk genes, revealing previously undetected exons and isoforms that may contribute to disease mechanisms.

This paper develops a ratio-based framework using Quartet reference materials to integrate long- and short-read RNA-seq data, showing hybrid-seq achieves the highest quantification accuracy.

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 study compares single-nucleus and single-cell RNA sequencing in human bone marrow mononuclear cells, identifying method-specific biases and trade-offs.

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

TIRE-seq streamlines RNA-seq workflows by integrating mRNA purification into library preparation, improving efficiency and data quality in perturbation studies.

The paper introduces scRaCH-seq, a method for single-cell long-read sequencing that improves detection of isoform usage and mutations in targeted genes, demonstrating its application in CLL samples.

BLAZE identifies 10x cell barcodes from long-read nanopore scRNA-seq data without requiring matched short-read data, outperforming existing tools in accuracy and reducing false positives.

NanoSplicer identifies splice junctions from Oxford Nanopore sequencing data without relying on short-read data or annotations, improving accuracy in high-error regions.