Soumya Raychaudhuri

The paper integrates GWAS with scATAC-seq and scRNA-seq data to identify disease-critical fetal and adult brain cell types for multiple traits.

This study identifies genetic variants associated with cellular morphology using high-content imaging and genomic data from iPSCs.

The paper identifies a regulatory pathway involving rs7034653, FRA2, and TRAF1 that explains how a non-coding variant increases risk of inflammatory arthritis.

This study identifies eQTLs in psoriatic skin that are modulated by local inflammation, showing that gene regulation is primarily influenced by skin-specific factors rather than systemic variables.

The paper shows adipocytes regulate fibroblast function through cortisol signaling, and their loss leads to fibroblast dysfunction in inflammatory diseases.

The paper identifies a non-coding variant that increases ICOS expression, leading to more T peripheral helper cells and contributing to autoimmune diseases.

This study identifies 20 genome-wide significant loci associated with serum IgA levels and finds genetic correlations with various immune and metabolic traits.

This paper introduces scDRS, a method to identify disease-associated cells in scRNA-seq data using polygenic risk scores, finding novel subpopulations linked to diseases like IBD and schizophrenia.

This paper provides a statistical genetics guide for imputing HLA alleles from genotype data and offers best practices for association testing to identify HLA variants driving complex diseases.

This study finds that higher Native Peruvian ancestry is associated with increased tuberculosis progression risk, independent of socio-demographic and environmental factors.

The paper identifies cell type specific driver genes in autism-associated copy number loci using cerebral organoids and validates findings with CRISPR/Cas9-edited mosaic organoids.

The paper investigates how HLA alleles influence TCR CDR3 composition and finds strong associations between HLA risk alleles and specific CDR3 amino acid features linked to autoimmune diseases.

The paper deconstructs RA synovium using single-cell data to identify six cell type abundance phenotypes associated with distinct inflammatory states.

This study conducts a trans-ancestry GWAS of rheumatoid arthritis, identifying 124 loci, 34 novel, and shows improved polygenic risk score performance across populations.

Symphony maps query cells to large reference atlases efficiently, enabling rapid identification of cell states and phenotypes across diverse datasets.

The paper identifies a sex-specific evolutionary interaction between ADCY9 and CETP variants associated with dalcetrapib response and cardiovascular traits.

The paper identifies state-dependent eQTLs in memory T cells by analyzing single-cell RNA and protein data from Peruvians, showing that gene regulation varies with cell states and disease-associated variants are enriched in these contexts.

The paper identifies a common inflammatory macrophage phenotype across severe COVID-19 and other inflammatory diseases, driven by IFN-γ and TNF-α, and suggests potential therapeutic targets.

This paper introduces CNA, a method to identify disease-associated cell states by analyzing transcriptional neighborhoods across samples, showing improved performance over cluster-based approaches in simulations and real datasets.

The paper develops a method to identify population-specific causal effect sizes in functionally important regions using trans-ethnic genetic correlations.

This study identifies shared and ethnicity-specific HLA associations with ulcerative colitis through trans-ethnic analysis of diverse populations.

This paper introduces cov-LDSC, a method to estimate heritability and its enrichment in tissue-specific gene sets in admixed populations, showing high concordance across populations but population-specific differences for some traits.

The paper introduces scPOST, a tool for estimating statistical power in single-cell studies, and shows that larger sample sizes, reduced batch effects, and lower cell state variability increase power to detect clinically associated cell state shifts.

The paper identifies HLA-B*55:01 as a genetic risk factor for penicillin allergy through genome-wide analysis of electronic health records and imputed HLA data.

A large-scale GWAS in 212,453 Japanese individuals identified 45 novel susceptibility loci for 22 diseases, highlighting the importance of non-European population studies.

The paper integrates thousands of epigenetic datasets into 707 cell-type regulatory annotations to improve the trans-ethnic portability of polygenic risk scores by prioritizing variants in IMPACT regulatory elements.

The paper identifies dynamic allele-specific expression changes in T cell activation, particularly in HLA genes, showing regulatory effects linked to autoimmune risk.

Harmony alternates diversity-penalized soft clustering with cluster-specific linear correction of PCA embeddings, integrating single-cell datasets over multiple covariates and handling 500,000 cells in 7.2GB of memory.