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Next-generation Sequencing

Next-generation Sequencing

The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
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Updated: Sep 9, 2025

Targeted DNA Methylation Analysis by Next-generation Sequencing

Targeted DNA Methylation Analysis by Next-generation Sequencing

Published on: February 24, 2015

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

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

|September 4, 2025

Summary

Researchers developed sample-agnostic easy regions for accurate short-read variant calling. This new resource improves variant filtering for human samples in research and clinical settings.

Keywords:

assembly pangenome variant calling

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Published on: May 22, 2018

Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

Short-read sequencing variant calling benchmarks are limited to confident regions, potentially yielding 10x higher error rates in untested human samples.
Existing 'easy region' sets for variant calling are often biased or do not account for non-reference samples.

Purpose of the Study:

To derive sample-agnostic easy regions for accurate short-read variant calling across diverse human genomes.
To provide a reliable resource for filtering spurious variant calls in human samples.

Main Methods:

Utilized hundreds of high-quality human genome assemblies to define new easy regions.
Ensured regions are sample-agnostic and balanced for coverage and ease of variant calling.

Main Results:

Developed sample-agnostic easy regions covering 88.2% of GRCh38 and 92.2% of coding regions.
These regions accurately identify 96.3% of pathogenic variants in ClinVar.
The method is adaptable for other human assemblies and species with multiple genome assemblies.

Conclusions:

This resource offers a powerful and convenient method for filtering inaccurate variant calls.
Facilitates improved variant calling accuracy in both clinical and research applications.