Sohini Ramachandran

From Wikipedia to AI: Measuring 25 years of synthesis of human genetics research in the public-facing information ecosystem

The paper analyzes how human genetics research is represented in Wikipedia and AI-generated encyclopedias over 25 years, finding frequent mentions of genetics in pages about ethnicity and nationality.

From Nuisance to Signal: Leveraging Close Relatives in Biobank-Scale Demographic Inference

This paper evaluates the impact of retaining close relatives on demographic inference using IBD-based methods and finds that retaining relatives reduces bias in Ne estimates.

Systematic clustering alignment and feature characterization for single-cell omics using ACE-OF-Clust

ACE-OF-Clust improves single-cell clustering by aligning results across methods and identifying informative features in scRNA-seq and spatial transcriptomics data.

WINDEX: A hierarchical integration of site- and window-based statistics for characterizing the footprint of positive selection in genome-wide population genetic data

WINDEX improves detection of positive selective sweeps by integrating site- and window-based statistics in population genetic data, showing improved localization and genome-wide estimates of selective pressures.

ML-MAGES: A machine learning framework for multivariate genetic association analyses with genes and effect size shrinkage

ML-MAGES uses machine learning to improve genetic association analysis by shrinking inflated effect sizes and clustering variant associations across multiple traits.

A rapid, accurate approach to inferring pedigrees in endogamous populations

This paper introduces a rapid algorithm for pedigree inference in endogamous populations, accurately distinguishing relationships and handling reticulations.

Population genetics meets ecology: a guide to individual-based simulations in continuous landscapes

This paper provides a guide to implementing individual-based simulations in continuous landscapes, focusing on population dynamics and ecological applications.

Phasing millions of samples achieves near perfect accuracy, enabling parent-of-origin classification of variants

The paper benchmarks haplotype phasing methods on large datasets and introduces HAPTIC, an inter-chromosomal phasing method achieving low error rates for parent-of-origin classification.

Discovering non-additive heritability using additive GWAS summary statistics

This paper introduces i-LDSC, an extension of LDSC that accounts for genetic interactions, showing it recovers additional genetic variance in 25 traits from UK Biobank and BioBank Japan.

Enabling interpretable machine learning for biological data with reliability scores

This paper introduces reliability scores to improve interpretability in biological machine learning by assessing classifier reliability in challenging scenarios.

Genetic structure correlates with ethnolinguistic diversity in eastern and southern Africa

This study examines genetic structure in African populations using ethnolinguistic data, finding that language classifications better capture genetic variation than geography alone.

Uncertainty Quantification in Variable Selection for Genetic Fine-Mapping using Bayesian Neural Networks

This paper introduces a Bayesian neural network approach for variable selection in genetic fine-mapping, showing improved identification of true effect variables in complex traits.

Enrichment analyses identify shared associations for 25 quantitative traits in over 600,000 individuals from seven diverse ancestries

The paper identifies 1,000 gene-level associations and conserved pathway associations for 25 traits across seven ancestries using enrichment analyses on large-scale GWA data.

Multi-scale Inference of Genetic Trait Architecture using Biologically Annotated Neural Networks

This paper introduces BANNs, a probabilistic framework for GWA studies that improves association mapping and enrichment analysis by incorporating biological annotations and variational inference.

Natural variation in the regulation of neurodevelopmental genes modifies flight performance in Drosophila

The paper identifies genetic modifiers of flight performance in Drosophila using the DGRP, finding additive and epistatic variants, whole genes, and network interactions, with implications for neurodevelopment and neurodegeneration.

Pathway Analysis within Multiple Human Ancestries Reveals Novel Signals for Epistasis in Complex Traits

The paper identifies epistatic genetic interactions in height and BMI using a novel region-based method across diverse UK Biobank subgroups, finding 245 enriched pathways with 67% in African ancestry.

Estimation of Non-null SNP Effect Size Distributions Enables the Detection of Enriched Genes Underlying Complex Traits

The paper introduces gene-ε, a method to detect enriched genes underlying complex traits by improving SNP effect size estimation and reducing false positives in genome-wide association studies.

Hierarchical clustering of gene-level association statistics reveals shared and differential genetic architecture among traits in the UK Biobank

The paper introduces WINGS, a method using hierarchical clustering to identify shared genetic architecture among multiple traits in the UK Biobank, finding 10 significant phenotype clusters.

Germline features associated with immune infiltration in solid tumors

The paper identifies germline genetic features associated with immune infiltration in solid tumors using TCGA data and develops a framework for studying inherited factors influencing immune microenvironment.

Characterization of prevalence and health consequences of uniparental disomy in four million individuals from the general population

The paper characterizes the prevalence and health consequences of uniparental disomy in four million individuals, identifying 675 cases and linking UPD of chromosome 22 to autism.

Bayesian Estimation of Population Size Changes by Sampling Tajima’s Trees

This paper introduces a Bayesian method called BESTT for inferring population size changes using Tajima’s coalescent, showing it is computationally efficient and accurate for both simulated and human data.

pong: fast analysis and visualization of latent clusters in population genetic data

pong provides a fast and accurate method for analyzing latent clusters in population genetic data, offering interactive visualization and outperforming existing tools.

Bayesian Nonparametric Inference of Population Size Changes from Sequential Genealogies

This paper introduces a Bayesian nonparametric method for inferring population size changes over time from genealogies, showing improved accuracy and uncertainty quantification compared to existing methods.