Hidewaki Nakagawa

COOBoostR uses extreme gradient boosting to predict tumor tissue or cell-of-origin using chromatin marks and mutation density data, outperforming random forest methods in speed and accuracy.

The paper analyzes HHV-6 integration in human genomes, identifies co-evolution with chr22q, and reports evidence of in vivo excision and reactivation.

A large-scale GWAS in 212,453 Japanese individuals identified 45 novel susceptibility loci for 22 diseases, highlighting the importance of non-European population studies.

The paper screens 12,503 Japanese CRC patients and 23,705 controls for germline variants in 27 cancer genes, finding 3.3% of patients have pathogenic variants linked to CRC risk.

The paper analyzes whole-genome sequencing data from cancer samples to identify genomic footprints of telomere maintenance mechanisms, finding specific telomere variant repeat patterns associated with ATRX/DAXX mutations.

The paper introduces the Cancer LncRNA Census (CLC), a curated resource of lncRNAs with causative roles in cancer, and shows their genomic and evolutionary features.

The paper examines how somatic structural variations affect TAD boundaries and gene regulation in human cancers using whole genome sequencing data.

This study characterizes mitochondrial genomes in 2,700 cancer patients across 37 types using whole-genome sequencing and RNA-seq, revealing mutational patterns, truncating mutations, and nuclear transfer of mitochondrial DNA.

This study analyzes chromothripsis in 2,658 cancers using whole-genome sequencing, finding it prevalent across multiple cancer types with complex structural alterations.

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

ActivePathways integrates multivariate omics data to identify enriched pathways, revealing cancer driver genes and prognostic pathways in breast cancer.

The paper uses whole-genome sequencing to predict cell-of-origin for primary liver cancers, finding heterogeneity in origin predictions across cancer types.

The paper introduces an R package for predicting tumor-specific neoantigens from various mutations and integrating additional biological information.

The paper quantifies immune-based counterselection of somatic mutations by analyzing their depletion in MHC class I-displayed peptides and shows that MHC alleles are incompletely dominant.

The paper analyzes immuno-genomic data across 31 cancer types to identify immune escape mechanisms and immuno-editing histories.

ALPHLARD is a Bayesian method for HLA genotyping from WGS data, achieving high accuracy and detecting rare variants and somatic mutations.

The paper describes the PCAWG project's large-scale analysis of cancer whole genomes across multiple computing environments, producing validated consensus variants for downstream research.

The paper identifies multiple mutational signatures linked to tobacco smoking in cancer, reflecting both direct and indirect effects of tobacco smoke on DNA damage and mutation processes.

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