Jun Inamo

CATaN maps gene regulatory programs that shape genetic risk across complex diseases

CATaN integrates TF-GRNs and transcriptomes to identify genetic risk components across complex diseases, finding 588 significant CC components enriched for SNP heritability.

scLASER: a robust framework for simulating and detecting time-dependent single-cell dynamics in longitudinal studies

scLASER simulates and detects time-dependent cellular dynamics in longitudinal studies, showing higher sensitivity than traditional methods in rare cell types and non-linear patterns.

Deep immune profiling pinpoints cellular and molecular drivers of lupus immunopathology

The paper identifies novel cell states and molecular profiles in lupus patients using single-cell data, linking them to disease severity and treatment outcomes.

Deep immunophenotyping reveals circulating activated lymphocytes in individuals at risk for rheumatoid arthritis

The paper identifies activated lymphocyte phenotypes in individuals at risk for rheumatoid arthritis using mass cytometry and develops an immunophenotype score to distinguish these individuals from controls.

CellPhenoX: An eXplainable Cell-specific machine learning method to predict clinical Phenotypes using single-cell multi-omics

CellPhenoX identifies cell-specific phenotypes linked to clinical outcomes using single-cell multi-omics data, demonstrating its ability to detect relevant phenotypes in diseases like COVID-19 and ulcerative colitis.

Single-cell based integrative analysis of transcriptomics and genetics reveals robust associations and complexities for inflammatory diseases

This study integrates GWAS and scRNA-seq to identify genetically relevant cell states in inflammatory diseases, finding scDRS outperforms scGWAS in capturing disease-relevant cellular heterogeneity.

Immune Isoform Atlas: Landscape of alternative splicing in human immune cells

The paper generates a comprehensive atlas of alternative splicing in human immune cells using long-read sequencing, identifies unannotated transcripts, and links isoforms to disease through quantitative trait loci and GWAS data.