Published November 19, 2023 | Version v2.2
Publication Open

Homepage of Haplotype-resolved assemblies and variant benchmark of a Chinese Quartet.

Creators

  • 1. Xi'an Jiaotong University

Description

Chinese Quartet Genome

The Quartet Project is designed for quality control in biological analysis in China. The samples in this project have been approved as standard reference materials by the State Administration for Market Regulation in China. In this repository, we provided high-quality genome and variant benchmarks for this quartet.

Samples

There are four samples in Chinse Quartet, including father (LCL7), mother (LCL8), and two monozygotic twin daughters (LCL5 and LCL6). This quartet family is from Taizhou in China. For more information of the quartet, please click here.

Data information

The Quartet multi-omics reference materials and data are publicly available and accessible. The recipients of the Reference Materials are highly encouraged to share their data with the community in order for to improve the evaluation of the technologies, pipelines, batch effects, and so on.

For genomic data, we generated 50x PacBio HiFi, 100x coverage of Oxford Nanopore, 30x coverage of ultra long Oxford Nanopore (only for LCL5), 100x PacBio CLR, 100x 10x genomics linked reads and BioNano. All raw data is available from public, if you want to use genomic data in this study, please download it from The Quartet Data Portal.

Assembly

Variant Benchmarks

Usage of variant benchmarks

If you want to use the variant benchmarks, please click here to check the pipeline we provided.

Citation

Jia P, Dong L, Yang X, Wang B, Wang T, Lin J, Wang S, Zhao X, Xu T, Che Y, et al: Haplotype-resolved assemblies and variant benchmark of a Chinese Quartet. bioRxiv 2022:2022.2009.2008.504083. PDF

Download the latest release

1 Assemblies

2 Variant benchmarks

Contributions

  • Software developers are encouraged to benchmark their software using our samples and data.
  • We also encourage the community to submit their assemblies and variant to improve the assemblies and variant benchmarks.
  • Please contact with Peng Jia (pengjia@stu.xjtu.edu.cn)

Contact

Files

xjtu-omics/ChineseQuartetGenome-v2.2.zip

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