Nathan D. Olson

This paper benchmarks 7 TR genotyping tools using Nanopore long-read data, finding that no single tool is best across all metrics, and that sequence-level accuracy is crucial for clinical and population studies.

T2T-HG002v1.1, a complete diploid HG002 assembly lacking detectable errors over 99.4% of its length, enables genome-based benchmarking of assemblies, sequencing reads, and phased variant calls.

Aardvark benchmarks genomic variant calling accuracy by comparing haplotype sequences with a basepair score, supporting multiple variant types and outperforming hap.py.

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 creates a long-read benchmark for genetic variants using a large pedigree, improving variant calling performance and introducing new truth sets for tandem repeats and structural variants.

The paper describes a comprehensive genomic dataset from a tumor-normal pair with broad consent, generated using multiple sequencing technologies for benchmarking somatic variant detection.

The paper creates a variant benchmark for X and Y chromosomes using a complete assembly of HG002, highlighting challenges in variant detection in complex regions.

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 uses long-read sequencing on 100 samples from the 1000 Genomes Project to identify structural variants and improve understanding of human genetic variation.

The paper introduces genomic stratifications for human reference genomes GRCh37, GRCh38, and T2T-CHM13v2.0 to benchmark variant caller performance in difficult regions.

StratoMod predicts variant calling errors using interpretable machine learning to help design better variant calling pipelines.

The paper benchmarks small and large variants in tandem repeats across 86 samples, creating a benchmark dataset and comparison method for TR variant calling.

The paper presents the complete sequence of a human Y chromosome, correcting errors in the GRCh38 reference and adding over 30 million base pairs.

The paper introduces Minigraph-Cactus, a pangenome pipeline that constructs pangenome graphs directly from whole-genome alignments, demonstrating improved performance in mapping and variant calling across human and Drosophila data.

The paper presents a draft human pangenome reference that improves variant discovery and structural variant detection compared to existing references.

The paper shows recombination between heterologous human acrocentric chromosomes using pangenome data, revealing pseudo-homologous regions linked to Robertsonian translocations.

The paper presents two methods for precision engineering of genetic sensors using large-scale data and machine learning to achieve quantitative dose-response specifications.

The paper evaluates sequencing and assembly methods to create high-quality diploid human genome assemblies, finding that long reads and haplotype sorting improve accuracy and completeness.

This paper expands genome benchmarking to include difficult-to-map regions using linked and long reads, identifying more false negatives in variant calling.

The paper evaluates variant calling in difficult genomic regions using short- and long-read sequencing, showing improved performance with new methods and multi-technology approaches.

A gapless 3.055 billion bp human genome from HiFi and ultra-long nanopore reads resolves all centromeric arrays and acrocentric p-arms, adding 182 Mbp of new sequence.

The T2T-CHM13 reference genome improves read mapping and variant calling across diverse samples, reducing false positives and enabling novel variant discovery.

This paper creates a comprehensive benchmark for challenging medically-relevant autosomal genes, improving variant recall from 8% to 100% by addressing reference-specific false duplications.

Dose-response curves for 62 472 LacI coding sequences train a recurrent network for EC50 and G∞, enable EC50 targeting within 1.25-fold, and reveal band-stop sensors.

The paper assembles and annotates a population-specific Ashkenazi human reference genome, showing improved contiguity and completeness compared to GRCh38.

This paper develops a long-read sequencing protocol to improve variant detection and genome assembly in a human genome, achieving high accuracy and contiguity.

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 presents high-coverage long-read sequencing data from a Han Chinese trio for developing and evaluating long-read bioinformatics methods.

The paper develops a reproducible pipeline to integrate sequencing datasets for high-confidence SNP, indel, and reference calls in five human genomes, showing improved variant detection compared to prior methods.

The paper introduces an R package for handling 16S rRNA databases and marker-gene survey data, providing consistent interfaces for database comparison and data structure development.