Ryan E. Mills

The paper assembles and characterizes 2,110 human centromeres, revealing novel haplotypes, mobile element insertions, and mutation rate variation across chromosomes.

This study assesses somatic mosaicism in human frontal cortex using multi-platform sequencing, showing improved variant detection with haplotype-resolved assemblies and single-neuron sequencing.

The paper develops a framework to detect and trace somatic retrotransposition events in human tissues, identifying rare L1 insertions and improving detection accuracy.

Hybrid HiFi/ultra-long ONT assemblies of 65 diverse humans yield 130 haplotypes, 1,246 complete centromeres, and a pangenome panel enabling short-read genome inference at median QV 45.

This paper uses domain-specific embeddings to uncover hidden genetic knowledge from scientific literature, predicting gene-disease associations and gene-gene interactions before they are published.

This paper introduces OGL, a deep learning method that integrates multi-omics data to predict gene expression and uncover regulatory interactions across cell lines and tissues.

The paper introduces NAHRwhals, a method to detect serial structural variations in long-read genomes, identifies 37 sSV loci in humans, and shows their relevance to disease.

The paper quantifies somatic mitochondrial DNA insertions (Numts) in human brain and fibroblasts, showing their accumulation over time and association with lifespan.

The paper identifies and validates copy number variants in single human neurons using a new method, revealing nonrandom CNV locations and complex karyotypes in a subset of neurons.

DeepMosaic detects mosaic single nucleotide variants without control samples using deep convolutional neural networks, achieving high accuracy and uncovering many variants missed by existing methods.

The paper presents a high coverage whole genome sequencing resource of 3,202 samples, including 602 trios, generated from the expanded 1000 Genomes Project.

Mako detects complex structural variants using a graph-based pattern growth approach, achieving 70% validation rate on real data and identifying 15 CSV types including two novel ones.

SearcHPV identifies and assembles HPV-host integration sites in cancer with higher sensitivity and specificity than existing methods.

The paper uses Cas9 targeted nanopore sequencing to enrich and detect mobile elements in human genomes, identifying non-reference MEIs missed by existing methods.

This study identifies somatic SNVs in non-cancerous human brain tissues and establishes best practices for detecting low-frequency variants.

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

SquiggleNet classifies nanopore signals in real time with high accuracy, outperforming traditional methods in speed and memory usage.

The paper introduces a machine learning method to detect somatic L1 insertions in human brain tissue, revealing their widespread distribution in neurons and glia and potential role in neuropsychiatric diseases.

This study provides genome-wide data for the Ukrainian population, identifying novel genetic variants and highlighting its unique genetic diversity.

The paper characterizes recent nuclear mitochondrial insertions (NumtS) in primate genomes, showing higher prevalence and rates in chimpanzees compared to other great apes.

The paper compares structural variant detection using short-read and long-read sequencing in three trios, showing lrWGS finds more SVs but srWGS has high concordance in non-repetitive regions.

Genome in a Bottle benchmark of 12745 sequence-resolved insertions and deletions of 50 bp or more, integrating 19 calling methods, scores false negatives and false positives alike.

The paper uses ribosome profiling to analyze uORF translation in neuronal differentiation, finding that uORFs correlate with repressed CDS translation and buffer CDS translation shifts.

This study identifies a large number of structural variants in human genomes using multiple sequencing technologies and presents them as a gold standard for future studies.

VaPoR validates structural variations using long-read sequencing data with high accuracy and efficiency, outperforming manual methods.

SVelter reconstructs complex structural genomic rearrangements by iteratively rearranging genome regions and scoring them against sequencing data.