five

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

收藏
DataCite Commons2025-08-13 更新2026-05-03 收录
下载链接:
http://gigadb.org/dataset/102750
下载链接
链接失效反馈
官方服务:
资源简介:
While benchmarks on short-read variant calling suggest low error rate below 0.5%, they are only applicable to predefined confident regions. For a human sample without such regions, the error rate could be 10 times higher. Although multiple sets of easy regions have been identified to alleviate the issue, they fail to consider non reference samples or are biased towards existing short-read data or aligners.<br>Here, using hundreds of high quality human assemblies, we derived a set of sample-agnostic easy regions where short-read variant calling reaches high accuracy. These regions cover 88.2% of GRCh38, 92.2% of coding regions and 96.3% of ClinVar pathogenic variants. They achieve a good balance between coverage and easiness and can be generated for other human assemblies or species with multiple well assembled genomes.<br>This resource provides a convient and powerful way to filter spurious variant calls for clinical or research human samples.
提供机构:
GigaScience Database
创建时间:
2025-08-13
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作