Noor Singh

The paper introduces mehenDi, a tree-based differential testing method for RNA-Seq that accounts for inferential uncertainty, improving detection of differentially expressed transcripts and inner nodes.

Oarfish improves long read transcriptome quantification by incorporating a novel coverage score into its probabilistic model, leading to more accurate quantification estimates.

Alevin-fry-atac provides a fast, memory-efficient method for single-cell ATAC-seq data processing with high accuracy compared to existing tools.

This study uses RNAi screening in C. elegans to identify rab-1 as essential for gonad morphogenesis but not stem cell niche maintenance.

The paper introduces a replicable benchmark for long-read transcript quantification tools and evaluates their performance on synthetic datasets.

Fulgor is a compact k-mer index for efficient sequence matching and color queries, outperforming existing methods in space and speed.

TreeTerminus groups transcripts into a tree structure to balance uncertainty and resolution for RNA-seq analysis, improving performance over transcripts and other methods.

The paper introduces SEESAW, a method to detect isoform-level allelic imbalance while accounting for inferential uncertainty, and evaluates it on simulated and real RNA-seq data.