Oliver Stegle

FISHFactor is a probabilistic factor model for spatial transcriptomics data that improves accuracy by modeling single molecule resolution data and sharing information across cells.

This study creates a spatially resolved single-cell multiomics atlas of human trophoblast differentiation in early pregnancy, revealing key regulatory programs and cell-cell communication events involved in EVT invasion and arterial transformation.

CellRegMap identifies context-specific regulatory variants using scRNA-seq by analyzing allelic effects across cell types and states.

pycoMeth provides a toolbox for differential methylation analysis of long-read ONT sequencing data, offering improved efficiency and performance over existing methods.

The paper introduces MUON, a framework for organizing, analyzing, and visualizing multimodal omics data, enabling flexible multi-omics analysis and interoperability with existing standards.

cell2location uses a Bayesian model to integrate single-cell and spatial transcriptomics, mapping cell types in situ across mouse brain regions and human lymph node immune compartments.

MEFISTO enables spatio-temporal dimensionality reduction and pattern separation in multi-modal genomic data, revealing conserved and diverged developmental programs and microbiome heterogeneity.

scDALI models allelic heterogeneity in single-cell chromatin accessibility to identify context-specific genetic regulation.

SpatialDE2 unifies tissue zone mapping and spatially variable gene detection for spatial transcriptomics within a fast Bayesian framework that directly models Poisson count noise.

IceR improves proteome coverage and data completeness in global and single-cell proteomics by combining DDA's identification rates with DIA's low missing value rates.

This study identifies indirect genetic effects (IGE) from peers in mice using igeGWAS and confirms IGE genes through knockout experiments.

This paper introduces SSAM, a cell segmentation-free method for cell-type identification and tissue domain detection in in situ transcriptomics data, showing it detects known and discovers new cell types in mouse brain tissues.

The paper uses single-cell RNA sequencing to study genetic variant effects on dopaminergic neuron differentiation from iPSCs, identifying eQTL and cell fate markers.

The paper maps regulatory effects of human disease variants in pluripotent cells, identifying cis- and trans-QTL across 18,556 genes and linking them to GWAS traits.

The paper presents 64 haplotype-resolved human genomes using long-read sequencing and identifies structural variants, SV-eQTLs, and adaptive selection candidates.

This study shows that humans integrate past and current sensory signals to estimate uncertainty, challenging models that assume uncertainty is based only on current stimuli.

This study identifies 5,106 new genetic variants associated with blood cell traits using large-scale GWAS, highlighting the polygenic and monogenic basis of hematopoiesis.

The paper characterizes proteome variation across 202 human iPSC lines, identifies 700 pQTLs, and links pQTLs to disease-associated GWAS variants.

The paper uses CRISPR-activation and single-cell RNA-seq to identify 44 epigenetic regulators that induce a zygotic genome activation-like state in mouse embryonic stem cells.

The paper examines how structural variants and short tandem repeats affect gene expression and complex traits, identifying high-impact variants associated with multiple genes and GWAS traits.

The paper discovers and genotypes a comprehensive set of structural variants and short tandem repeats using multiple algorithms and replicates, creating a well-characterized map of these variants.

MOFA+ integrates structured single-cell multi-modal data by modeling group and view structures, revealing coordinated gene expression and epigenetic changes during mouse gastrulation.

This study benchmarks 13 scRNA-seq protocols to evaluate their effectiveness in characterizing cell types and states for cell atlas projects.

The paper shows that erosion of X chromosome inactivation in human iPSCs leads to increased protein expression from X-linked and autosomal genes, altering protein-RNA correlations and increasing protein content.

The paper benchmarks bulk functional genomics tools on scRNA-seq data, showing comparable performance to bulk data and suggesting their applicability over dedicated single-cell tools.

The paper uses single-cell RNA-seq of differentiating iPS cells from 125 donors to identify expression quantitative trait loci influencing gene expression during endoderm differentiation.

The paper identifies hundreds of genes deregulated by SVs in cancer, showing increased expression linked to SV breakpoints and enhancer elements.

This study performs GWAS on blood cell flow-cytometry phenotypes, identifies variant-trait associations, and links them to cellular structures and disease mechanisms.

The paper identifies novel BMI genotype-environment interactions using a conditional false discovery rate approach on UK Biobank data, finding 140 candidate loci with GxE effects.

This study uses regulatory QTLs from immune cells to fine-map causal variants for twelve immune-mediated diseases, finding smaller credible sets and higher posterior probabilities compared to traditional methods.