Bayesian inference

Excluded causal variants produce false discoveries in genetic fine-mapping

This study shows that excluding low-frequency variants and indels in fine-mapping leads to false discoveries and introduces SuSiE-OUT to address this issue.

Single-Cell Transcriptome-Wide Mendelian Randomization and Colocalization Analysis Reveals Immune Cell-Specific Mechanisms in Alzheimer's Disease

This paper uses single-cell eQTL-MR and colocalization analysis to identify immune cell-specific genetic mechanisms associated with Alzheimer's disease risk.

The behaviour bends, the code holds: working-memory category information in the multiple-demand network across graded interruption

This study investigates how the multiple-demand network maintains working memory during task interruptions, finding that neural representations of category information remain stable despite behavioral costs.

A single day of natural daylight exposure and physical activity does not conclusively change circadian phase: A Bayesian crossover experiment

This study investigates the effects of natural daylight and physical activity on circadian phase using a Bayesian crossover experiment, finding inconclusive results.

The Segmentome: a novel representation of the DNA methylome identified by a Bayesian HMM framework

The paper introduces the segmentome, a DNA methylome representation using a Bayesian HMM, and shows it can group cell types and identify cell-of-origin in DNA samples.

Plasma Proteogenomics Identifies RGMB as a Candidate for Primary Open-Angle Glaucoma Detected Only in East Asians

The paper identifies RGMB as a potential risk factor for East Asian POAG through proteogenomic analysis, showing ancestry-specific associations and lack of colocalization with IOP traits.

Single-cell transcriptome-wide Mendelian randomization and colocalization analyses reveal immune-cell-specific mechanisms and actionable drug targets in prostate cancer

The paper identifies immune-cell-specific genetic associations and drug targets in prostate cancer using integrative analyses of single-cell and bulk data.

SPARK: Bayesian structure learning of enhancer-based gene regulatory networks from single-cell multiomics data and prior knowledge

SPARK reconstructs enhancer-based gene regulatory networks using single-cell multiomics data and prior knowledge, revealing regulatory links associated with immune disease GWAS variants.

A clinically annotated proteomic and histological resource of 1,000 colorectal cancers

Deep proteomics of 997 treatment-naïve colorectal cancers defines six subgroups, splitting chromosomally unstable tumors into three and revealing a rare adverse subgroup, with H&E slide benchmarks.

abcneuralnet: Simulation-based Inference with Bayesian Neural Networks and Explainable AI for Population Genomics Inference

abcneuralnet provides a Bayesian Neural Network framework with explainable AI for population genomics inference, offering calibrated prediction intervals and uncertainty decomposition.

Using Bayesian inference to characterize cell-size regulation across organisms

This paper develops a Bayesian framework to accurately infer cell-size regulation strategies by accounting for noise and variability, showing that previous methods were biased and that adder-like regulation is more consistent across organisms.

Joint Variable Selection for Omic Biomarkers in Time-to-Event Data

The paper introduces vampW, a Bayesian method for joint variable selection in omic biomarkers and time-to-event data, showing reduced false discoveries and improved prediction.

Covariance Nonstationarity is Evident in Spatial Transcriptomics and Provides a New Categorization of Spatially Varying Genes

The paper assesses covariance stationarity in spatial transcriptomics and identifies spatially varying genes using non-stationary covariance models.

Application of Bayesian-Derived Gene Interaction Network and Subnetwork for Classification of Idiopathic Parkinson Disease with Biomarkers

The paper develops a Bayesian gene interaction network to identify 13 genes for PD classification, achieving high AUC in a blood-based transcriptomic analysis of the PPMI cohort.

Retinal arteriolar tortuosity as a candidate genetic window to inner-ear microvasculature: distributed sharing with blood pressure at CSK and PAWR and a roadmap for larger hearing GWAS

This paper investigates the genetic link between retinal arteriolar tortuosity and blood pressure, identifying potential shared genetic loci and suggesting retinal microvasculature as a candidate window for inner-ear microvasculature studies.

A Bayesian approach to volumetric analysis in rare neurodegenerative disorders

This paper applies Bayesian hierarchical modeling to assess regional brain atrophy in rare neurodegenerative disorders, finding significant volume loss in specific brain regions across disease groups.

Gene-level evolutionary conservation and human constraint decline at comparable rates across the age of onset of Mendelian disease

The paper compares the rate of decline in gene-level evolutionary conservation and human constraint scores with disease onset age across Mendelian diseases.

Taking a BREATH (Bayesian Reconstruction and Evolutionary Analysis of Transmission Histories) to simultaneously infer phylogenetic and transmission trees for partially sampled outbreaks

BREATH simultaneously infers phylogenetic and transmission trees for outbreaks using sequence data, improving resolution and origin timing estimates in a tuberculosis outbreak.

Multi-Trajectory Pseudotime Inference via Permutation Factorizations

Factorizing multiple monotone pseudotimes into one shared donor permutation plus cluster-specific warps (HiP-BIND) yields Alzheimer's donor orderings agreeing better with Braak, ADNC and CERAD staging than single-trajectory B-BIND.

LGTM: Gaussian Process Modulated Neural Topic Modeling for Longitudinal Microbiome

LGTM couples a neural topic model with additive basis-function Gaussian processes, learning microbial co-abundance topics and how covariates relate to their trajectories in longitudinal gut microbiome data.

An information-borrowing Bayesian method for inferring high-dimensional population-level brain connectivity from small samples

The paper introduces a Bayesian method for estimating population-level brain connectivity from small samples, showing improved accuracy over existing methods in simulations and real data.

Accurate detection of metagenomic strain-level associations using average nucleotide identity with StrainSpy

StrainSpy fits zero-inflated beta mixed models to containment ANI, reaching >98% simulated sensitivity versus ~79% for logistic regression and detecting colorectal-cancer E. coli strain shifts.

SFUMATO: Bayesian probabilistic clustering for uncertainty-aware spatialtranscriptomics analysis and mapping

SFUMATO provides a Bayesian probabilistic framework for spatial transcriptomics that captures uncertainty and enables continuous visualization of transcriptional domains.

The prevalence of protein misfolding as a mechanism for hereditary deafness

The paper evaluates computational frameworks to prioritize pathogenic variants in deafness-associated genes, identifying 28,866 VUSs with high pathogenicity probability and improving diagnoses for 12 patients.

Normative Modeling of Molecular-Enriched Functional Connectivity for Detecting Deviations from Healthy Brain Aging

This paper develops normative models to detect deviations in molecular-enriched functional connectivity associated with amyloid burden in healthy aging brains.

Estimating conditional cell population associations across tumor density trajectory in three dimensional tissue images

The paper introduces ISPat-3D to estimate conditional cell population associations in 3D tissue images, finding stable associations in colorectal cancer but less stable in breast cancer.

Dissecting shared genetic susceptibility between gastroesophageal reflux disease and psychiatric disorders beyond body mass index

This study identifies shared genetic factors between GERD and psychiatric disorders, showing stronger links with internalizing disorders than with BMI.

A Bayesian framework reveals heterogeneous and stochastic decision-making in NK cell cytotoxicity

This study develops a Bayesian framework to analyze NK cell cytotoxicity and identifies distinct mechanisms underlying variability in killing responses.

TCF25 emerges as a cytoplasmic regulator of GPRASP2 stability

TCF25 is mostly cytoplasmic with a perinuclear membrane-proximal pool, stabilises GPRASP2 against proteasomal degradation, and its C-terminal residues 604-664 are required for their association.

A Bayesian modelling framework for inference of latent infection risk patterns from virus neutralisation assay titration data

The paper introduces a Bayesian framework to infer latent infection risk patterns from virus neutralisation assay titration data, revealing higher and more persistent antibody concentrations for EV-D68 compared to other viruses.