Roozbeh Dehghannasiri

This study shows that RNase H1 reduces DNA damage and improves SMA-like symptoms in a Drosophila model by resolving RNA:DNA hybrids caused by SMN deficiency.

sc-SPLASH enables reference-free discovery in scRNA-seq and spatial transcriptomics, uncovering novel transcriptomic features like V(D)J recombination and secreted repeat proteins.

The paper benchmarks 16 circRNA detection tools across three human cell types, finding large differences in sensitivity but consistent precision, and recommends tool combinations for improved detection.

SPLASH2 is an efficient, scalable algorithm for discovering regulated sequence variation in RNA-seq data, revealing new biology in single-cell and bulk datasets without parameter tuning.

SPLASH+ identifies novel transcriptomic diversity in human single cells without reference genomes or cell type metadata.

ReadZS identifies cell type-specific and developmentally regulated RNA processing programs in single-cell RNA-seq without relying on pre-existing annotations.

This paper uses a mouse lemur transcriptomic atlas to identify new genes, splice junctions, and disease-related features, highlighting their relevance to primate biology and human disease.

Portal integrates large-scale single-cell datasets efficiently and accurately by preserving biological variation across samples, platforms, and species.

This paper identifies activated interstitial macrophages as a key target of SARS-CoV-2 infection in human lung tissue, showing their role in viral takeover, inflammation, and fibrosis.

The paper introduces SpliZ and SpliZVD, statistical methods to detect regulated splicing in single-cell RNA-seq, revealing new cell-type-specific splicing events in human lung cells.

The paper introduces SpliZ, a statistical method to detect cell-type-specific splicing regulation in single-cell RNA-seq data, finding 9.1% of genes show such regulation in human tissues.

SICILIAN improves splice junction detection in scRNA-seq by assigning statistical confidence, enhancing accuracy and agreement with bulk data and biological replicates.

This study shows TGS1 is essential for snRNA 3' end processing and its loss causes neurodegeneration, which can be mitigated by human TGS1 expression in model organisms.

DEEPEST improves gene fusion detection in cancer by reducing false positives and identifying new oncogenic RNA drivers using statistical methods.