Dheeraj Malhotra

The paper identifies cis and trans gene regulatory mechanisms in microglia linked to multiple sclerosis risk SNPs using computational and CRISPR perturbation approaches.

The paper uses single-cell Mendelian randomisation to identify cell-type specific genetic effects on brain disease and behaviour, revealing 118 genes with causal associations to 16 brain phenotypes.

The paper uses single nuclei RNAseq to identify distinct glial gene expression patterns in MS patients, revealing subgroup-specific pathological processes and suggesting precision medicine approaches.

This study uses single-nucleus and spatial transcriptomics to identify cell type-specific associations with Alzheimer's disease pathology in human temporal cortex and white matter.

The paper uses single-cell genomics to identify shared and disease-specific cell states and gene regulatory networks in three dementias, revealing distinct neuroimmune mechanisms and potential therapeutic targets.

This study identifies somatic copy number variants (sCNVs) in schizophrenia cases, revealing their contribution to risk and specific NRXN1 disruptions.

This study evaluates a cryopreservation protocol for CSF cells, showing it preserves cell composition and transcriptomes effectively, enabling multi-center research.

The paper investigates the conservation of rare schizophrenia risk variants across diverse populations and finds consistent burden in constrained genes.

CellMixS quantifies and visualizes batch effects in scRNA-seq data by developing a cell-specific mixing score and comparing metrics for their performance.

This paper develops a simulation platform and analysis tools for multi-condition differential state analysis in scRNA-seq data, comparing cell-level mixed models and pseudobulk approaches.

The paper introduces a junction coverage compatibility score to assess the reliability of transcript abundance estimates and annotation catalogs by comparing observed and predicted junction-spanning reads.

The paper identifies 1.2 million structural variants in 235 individuals, showing high de novo mutation diversity and complex mutation clusters, but finds no increased genome rearrangement rate for ASD.