Ai Okada

Personalized reference genome-based pipeline reveals comprehensive haplotype-resolved views of cancer genomes

PRCGAP provides a haplotype-resolved analysis of cancer genomes, detecting variants missed by standard references and revealing new insights into structural variants and fusion events in leukemia.

CrosSplice: A Pipeline for Identifying Rare Splice-Site Creating Variants from Cross-Tissue Transcriptome Data

CrosSplice identifies rare splice-site creating variants using cross-tissue transcriptome data, discovering clinically relevant variants missed by conventional methods.

Rare k-mers reveal centromere haplogroups underlying human diversity and cancer translocations

This paper uses rare k-mers to identify centromere haplogroups in human populations and cancer translocations, revealing structural diversity and translocation mechanisms.

Systematically developing a registry of splice-site creating variants utilizing massive publicly available transcriptome sequence data

The paper develops a framework to identify splice-site creating variants (SSCVs) using transcriptome data, identifies 30,130 SSCVs, and demonstrates their therapeutic potential with ASOs.

Precise characterization of somatic complex structural variations from paired long-read sequencing data with nanomonsv

nanomonsv detects somatic structural variations from long-read sequencing data with high precision and recall, revealing complex SV features in cancer.

A comprehensive workflow for target adaptive sampling long-read sequencing applied to hereditary cancer patient genomes

This study develops a computational workflow for target adaptive sampling long-read sequencing and applies it to hereditary cancer genomes to identify genetic variants and epigenetic changes.

Systematic identification of intron retention associated variants from massive publicly available transcriptome sequencing data

The paper identifies intron retention associated variants using transcriptome data alone, finding 27,937 variants and 3,077 putative disease-associated ones.

SF3B1ness score: screening SF3B1 mutation status from over 60,000 transcriptomes based on a machine learning approach

The paper develops SF3B1ness score to predict SF3B1 mutation status from transcriptomes using machine learning, achieving high precision and sensitivity in identifying functional mutations.

A comprehensive characterization of cis-acting splicing-associated variants in human cancer

The paper identifies and characterizes splicing-associated variants in cancer using a statistical framework applied to 8,976 samples across 31 cancer types, revealing 14,438 SAVs and their association with smoking and tumor suppressors.

A framework for generating interactive reports for cancer genome analysis

The paper introduces paplot, a software tool for generating interactive reports in cancer genome analysis, enabling richer data exploration than static visualizations.