Takafumi N. Yamaguchi

The paper identifies a high-performance state in esports using pupil-heart synchrony, showing it correlates with objective performance despite lower subjective workload.

This study maps epigenomic heterogeneity in prostate cancer by analyzing 3,001 methylomes and identifies four subtypes with distinct clinical and molecular features.

This paper presents near-complete, haplotype-resolved assemblies of a pancreatic cancer genome and normal tissue, identifying extensive somatic variants and epigenetic changes in previously excluded regions.

The paper analyzes genetic and health record data from a diverse population to uncover gene-phenotype associations and assess polygenic score performance across ancestries.

Metapipeline-DNA automates comprehensive analysis of DNA sequencing data from raw reads to visualization, supporting germline and somatic genomic features.

This study quantifies mutation rates, selection coefficients, and epistatic interactions across prostate cancer stages, revealing dynamic selective pressures and therapeutic implications.

This study examines how live sports spectating affects endogenous oxytocin and heart rate synchrony, linking these to social bonding and psychological outcomes in a collegiate setting.

moPepGen identifies non-canonical peptides from genetic and transcriptomic data across species and technologies by generating them in linear time.

This study demonstrates that RNA transcripts can serve as templates for double-strand break repair in human cells, identifying DNA polymerase-zeta as a key enzyme and revealing genomic scars associated with this process.

The paper develops a benchmark for detecting low-frequency mosaic variants in the HG002 reference material using high-coverage sequencing data and validates its utility across multiple technologies.

The paper quantifies the impact of genome build differences on variant calling and introduces StableLift, an algorithm to predict cross-build variant stability.

This study examines telomere length in prostate cancer, finding associations with genomic instability and clinical outcomes.

The paper benchmarks somatic structural variant detection methods using synthetic tumors and crowd-sourced submissions, finding that ensembles do not always outperform individual methods.

Valection optimizes the selection of verification candidates to estimate error profiles in genomics studies by evaluating different strategies on synthetic data.

S22S is a reference-free method for somatic variant calling that uses genomic and population data to accurately identify SNVs without matched normal samples.

The paper quantifies germline leakage in somatic SNV detection across 259 datasets and introduces a tool to correct it, finding low leakage rates that can be further reduced with pre-filtering.

This study compares whole genome sequencing pipelines across five centers using a uniform tumor-normal sample pair, identifying factors affecting output consistency.