ArticleNature communications2024
The GIAB genomic stratifications resource for human reference genomes.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.
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Who cites it
53 citing papers in PubMed.
- Telomere-to-telomere CHM13 reference reveals missing truth variants and improves deep learning-based variant calling in long-read sequencing data.Quantitative biology (Beijing, China) · 2026Article
- An Icelandic pangenome reference.Nature · 2026Article
- Defining and cataloging variants in pangenome graphs.Cell genomics · 2026Article
- The promise of long-read RNA-seq: reducing bias in analyses of allele imbalance.NAR genomics and bioinformatics · 2026Article
- Assessing Hardy-Weinberg equilibrium in T2T-aligned 1000 genomes project.PLoS genetics · 2026Article
- Long-read based detection of large copy number variants with potential functional significance using the ContextSV structural variant caller.NAR genomics and bioinformatics · 2026Article
- ONT-only genome assembly of a Korean male individual using a semen sample.Genes & genomics · 2026Article
- ClairS: a deep-learning method for long-read tumor-normal pair somatic small variant calling.Nature methods · 2026Article
- HPRC2: A human pangenome reference with near-complete coverage of common genetic variation.bioRxiv : the preprint server for biology · 2026Article
- Pangenome-based human genome analysis improves trait association and genomic prediction.bioRxiv : the preprint server for biology · 2026Article
- needLR: long-read structural variant annotation with population-scale frequency estimation.Bioinformatics (Oxford, England) · 2026Article
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- Short-Read Sequencing Benchmarking with Donor-Specific Assemblies.bioRxiv : the preprint server for biology · 2026Article
- Whole-genome sequencing with AVITI and NovaSeq X Plus reveals comparable performance with contextual biases.NAR genomics and bioinformatics · 2026Article
- Whole genome sequencing of pre-treatment and post-treatment locally advanced rectal cancer using long and short read technologies.Scientific reports · 2026Article
- A sibling study of variation in parental mutation rates.bioRxiv : the preprint server for biology · 2026Article
- Functional impact of genetic background on variable expressivity in neurodevelopmental disorders.Nature communications · 2026Article
- Global impact of germline structural variation on the cancer proteome.Nature communications · 2026Article
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14 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Despite the growing variety of sequencing and variant-calling tools, no workflow performs equally well across the entire human genome. Understanding context-dependent performance is critical for enabling researchers, clinicians, and developers to make informed tradeoffs when selecting sequencing hardware and software. Here we describe a set of "stratifications," which are BED files that define distinct contexts throughout the genome. We define these for GRCh37/38 as well as the new T2T-CHM13 reference, adding many new hard-to-sequence regions which are critical for understanding performance as the field progresses. Specifically, we highlight the increase in hard-to-map and GC-rich stratifications in CHM13 relative to the previous references. We then compare the benchmarking performance with each reference and show the performance penalty brought about by these additional difficult regions in CHM13. Additionally, we demonstrate how the stratifications can track context-specific improvements over different platform iterations, using Oxford Nanopore Technologies as an example. The means to generate these stratifications are available as a snakemake pipeline at https://github.com/usnistgov/giab-stratifications . We anticipate this being useful in enabling precise risk-reward calculations when building sequencing pipelines for any of the commonly-used reference genomes.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.