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Updated: Sep 11, 2025

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

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Finding easy regions for short-read variant calling from pangenome data.

¹Department of Biomedical Informatics, Harvard Medical School, 10 Shattuck St, Boston, MA 02215, USA.

|August 13, 2025

Summary

New sample-agnostic easy regions improve short-read variant calling accuracy for human genomes. This resource enhances variant filtering for clinical and research applications, overcoming limitations of previous methods.

Keywords:

assembly pangenome variant calling

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Last Updated: Sep 11, 2025

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

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Targeted DNA Methylation Analysis by Next-generation Sequencing

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Published on: February 24, 2015

Area of Science:

Genomics
Bioinformatics
Population Genetics

Background:

Short-read variant calling benchmarks often use predefined confident regions, potentially underestimating error rates in non-reference human samples.
Existing 'easy region' sets may not account for sample-specific variations or are biased by specific aligners and short-read data.
High error rates in non-confident regions can hinder accurate variant identification in clinical and research settings.

Purpose of the Study:

To develop a comprehensive set of sample-agnostic easy regions for accurate short-read variant calling across diverse human genomes.
To provide a robust resource for filtering spurious variant calls in both clinical and research contexts.
To establish a method for generating similar regions for other species or assemblies.

Main Methods:

Leveraged hundreds of high-quality human genome assemblies to identify and define sample-agnostic easy regions.
Evaluated the performance of variant calling within these derived regions.
Assessed the coverage of key genomic features, including coding regions and pathogenic variants.

Main Results:

Developed sample-agnostic easy regions that enable high-accuracy short-read variant calling.
These regions cover a significant portion of the human genome (88.2% of GRCh38), including 92.2% of coding regions and 96.3% of ClinVar pathogenic variants.
The identified regions offer a favorable balance between genomic coverage and ease of variant calling.

Conclusions:

The derived easy regions offer a powerful and convenient method for filtering inaccurate variant calls in human samples.
This resource is applicable to both clinical diagnostics and fundamental research, improving the reliability of variant data.
The methodology is adaptable for generating similar resources for other species or human assemblies.