Jennifer McDaniel

The paper uses long-read sequencing to characterize lentiviral provirus insertions in clonal CAR-T cell lines, revealing structural variations missed by short-read and ddPCR methods.

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

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 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.

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.

This paper introduces GROC-SVs, a method for detecting and assembling structural variants using read cloud data, showing improved specificity and enabling complex breakpoint reconstruction in cancer samples.

The paper evaluates ERCC RNA controls using a modified Latin square design across multiple platforms to assess their performance in quantifying RNA transcripts.

The paper presents extensive sequencing data from seven human genomes to serve as benchmark reference materials for improving sequencing technologies and variant calling.

The paper evaluates using RNA-seq mixtures as process controls to benchmark measurement performance and assess bias and variability.