Michael I. Love

splicelogic converts transcript-set comparisons into interpretable splicing events, enabling downstream analysis of isoform changes in RNA-seq data.

The paper uses CRISPR-based functional genomics to identify noncoding regulatory elements and variants affecting schizophrenia-associated gene expression.

The paper introduces standardized formats and tools for processing MPRA data to improve reproducibility and integration across studies.

The paper integrates social risk factors with genetic risk scores to improve bipolar disorder prediction in the All of Us Research Program, finding social factors have larger effect sizes than genetic risk.

R package DetectGxT fits allelic-additivity nonlinear models with optional donor or polygenic random effects, raising simulated power to detect gene-by-treatment interaction QTLs over linear regression.

The paper introduces a standard for unambiguously representing, retrieving, and comparing reference genomes and transcriptomes, revealing inconsistencies across 60 human and 36 mouse references.

This study uses Prime Editors in zebrafish to achieve precise DNA insertion and substitution without exogenous donor DNA, showing higher efficiency for short modifications with nuclease-based PEn.

The paper introduces plyxp, an R package that provides a grammar for efficiently manipulating annotated matrix data in the Bioconductor ecosystem.

This study uses single-nucleus multi-omics to analyze the developing Down syndrome neocortex, identifying dysregulated molecular and gene-regulatory mechanisms affecting neurogenesis and cell specification.

The paper uses long-read RNA-seq to create a comprehensive placental transcriptome reference, revealing high transcriptional complexity and identifying novel isoforms associated with metabolic and endocrine functions in gestational diabetes.

This paper shows that astrocytes reprogram neuronal gene expression and chromatin accessibility, affecting thousands of genes and regulatory elements, including those linked to schizophrenia and Alzheimer's disease.

The paper shows larger eQTL studies detect more signals that colocalize with GWAS signals, improving understanding of gene-trait relationships.

This study identifies hundreds of new cis-regulatory element-gene connections in the MHC locus using CRISPR screens and single-cell transcriptomics, revealing cell type-specific regulatory mechanisms.

The paper introduces GPSEA, a tool using GA4GH Phenopackets to analyze genotype-phenotype correlations in Mendelian disorders, identifying 225 significant associations across 85 cohorts.

The paper introduces mehenDi, a tree-based differential testing method for RNA-Seq that accounts for inferential uncertainty, improving detection of differentially expressed transcripts and inner nodes.

This paper introduces a method to classify gene-by-treatment interactions using Bayesian model selection and applies it to molecular count phenotypes with a software package.

This study benchmarks Nanopore long read RNA sequencing in human cell lines, showing improved isoform resolution compared to short reads.

The paper links early cell cycle gene expression in cortical organoids to interindividual variability in infant brain growth trajectories.

The paper introduces Consenrich, a method for robust signal recovery from multi-sample functional genomics data, showing improved biological insights in Alzheimer's cohort analysis.

The paper identifies OA risk genes by integrating eQTLs, chromatin accessibility, and 3D chromatin structure in human chondrocytes, revealing 13 putative risk genes, 10 of which are novel.

The paper benchmarks methods for prioritizing GWAS target genes using eQTLs and finds that assigning pQTLs to closest protein-coding genes outperforms colocalisation methods.

This study shows that human cortical organoids generated across multiple sites using a harmonized protocol consistently produce similar cell types and structures, though with some site-specific differences in size and stress markers.

The paper identifies cell-type-specific genetic regulation of RNA-editing and alternative polyadenylation in human neural progenitors and neurons, linking these to brain-related traits.

The paper introduces tidyomics, an ecosystem bridging Bioconductor and tidy R to streamline omic analysis using data from the Human Cell Atlas.

This paper improves variant effect quantification in base editing screens by integrating genotypic and phenotypic data using a Bayesian network called BEAN.

This paper introduces launch-dCas9, a machine learning framework to predict guide RNA effects in CRISPR epigenome editing, showing high accuracy and improved gRNA selection.

The paper identifies additional eQTL signals in adipose tissue and shows they contribute to cardiometabolic traits through gene dosage effects.

The paper uses MPRA to identify functional regulatory variants associated with schizophrenia and shows they differ from eQTLs in genomic location and regulatory impact.

The paper identifies differential chromatin loops during megakaryocyte differentiation and shows their association with gene expression changes and histone modifications.

The paper evaluates ten differential expression methods for metatranscriptomics data using real and simulated datasets, finding the logistic-beta test has highest sensitivity and reasonable type I error control.