Fritz Joachim Sedlazeck

The paper analyzes genetic variation, ancestry, and DNA methylation in Hispanic/Latino participants using long-read sequencing, identifying novel variants and phenotype associations.

IsoMatch integrates transcript models across references, showing how reference choice affects estimates of transcript novelty.

Isocall is a scalable method for joint transcript identification from long-read RNA-seq data, showing high precision and handling large datasets efficiently.

Himito is a graph-based toolkit for analyzing mitochondrial genomes using long reads, achieving superior performance in assembly and variant calling and revealing age-related patterns in the All of Us dataset.

SniffCell assigns somatic variants to cell types using DNA methylation from bulk long-read sequencing, revealing cell-type-specific mutations in human tissues.

The paper presents an integrated analysis of somatic mosaicism across 25 individuals, revealing tissue-specific mutational processes and epigenetic states.

SALRR provides a scalable platform for long-read RNA-seq analysis, identifying novel splice variants in human brain tissue.

IsoAtlas provides an interactive database for visualizing and interpreting transcript isoforms using long-read RNA-seq data from humans and mice.

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.

This study uses long-read sequencing to map transposable element variation in human brain tissue, revealing regulatory and epigenetic effects across cell types and ancestries.

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.

Omni2Tree directly analyzes raw sequencing reads to reconstruct viral phylogenies and identify diversification, outperforming assembly and reference-based methods in low-coverage scenarios.

The paper introduces a computational model to quantify tandem repeat instability using long-read sequencing data and applies it to identify unstable alleles in 256 HPRC cell lines.

Isopedia reduces apparent isoform novelty by up to 26-fold in HG002 benchmarks and provides a reference-agnostic framework for population-scale isoform annotation.

TumorLens detects genetic and epigenetic alterations in cancer using long reads, revealing key somatic events and methylation patterns across tumor samples.

This study evaluates Oxford Nanopore sequencing's performance in clinical genomics using reference samples, showing high accuracy for SNVs and SVs but challenges with INDELs and CNVs.

The paper introduces DRAGEN, a scalable mosaic variant caller that detects low VAF variants with high accuracy and efficiency, and presents a benchmark for low-VAF variants.

This study benchmarks machine learning methods for structural variant filtering in long-read sequencing data, finding that simple models match complex ones in accuracy.

VACmap improves detection of complex genomic rearrangements like inversions and duplications, which are critical for understanding diseases such as cardiovascular disease and Parkinson's disease.

Clair3-RNA is a deep learning variant caller for long-read RNA sequencing data that achieves high accuracy in SNP detection across different platforms.

MosaicSim simulates mosaic variants in sequencing data to evaluate detection methods, showing that higher coverage improves detection rates without false positives.

The paper presents a benchmark for detecting simple and complex genome inversions using Strand-seq and long-read assemblies, revealing method strengths and limitations across sequencing platforms.

TBAS enables cost-effective long-read sequencing of rare-disease trios with high variant detection accuracy and a 77% potential solve rate.

This paper evaluates Illumina Constellation sequencing for rare disease research, showing it can detect structural variants and haplotype phasing with low DNA input and existing infrastructure.

The paper analyzes long-read sequencing data from the All of Us Research Program to identify structural variants and their associations with diseases in a large cohort of Black or African American participants.

The paper benchmarks somatic structural variant detection at ultra-low allele fractions using synthetic data and evaluates 12 pipelines, finding long-read sequencing provides higher accuracy than short-read methods.

This study analyzes RSV evolutionary dynamics across pre-pandemic, pandemic, and post-pandemic periods in Houston, finding reduced diversity during the pandemic and increased non-synonymous mutations in RSV/B.

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.

This paper introduces a method called kanpig for accurately genotyping structural variants using long-read alignment pileups, achieving higher concordance than existing tools.