CMDB

CMDB provides a curated catalogue of 9.04 million single nucleotide variants (SNVs) with allele frequency and genic annotation information derived from low-coverage (0.06×–0.1×) whole-genome sequencing to support population and translational genomics research.

Key Features:

• Variant catalogue: Contains 9.04 million single nucleotide variants (SNVs) with allele frequency information.
• Sequencing depth: Variant data derived from low-coverage (0.06×–0.1×) whole-genome sequencing (WGS).
• Cohort size: Aggregates data from 141,431 unrelated healthy individuals.
• Population coverage: Samples include participants from 31 of 34 Chinese administrative divisions, covering Han and 36 minority groups.
• Genic annotations: Provides variant-level genic annotations.
• Global frequency comparison: Offers overview comparisons of variant frequencies in global populations.
• Phenotype associations: Reports associations between specific SNVs and phenotypes including height, body mass index (BMI), maternal age, and twin pregnancy outcomes.
• Searchable variant access: Enables retrieval of basic mutation data, allele frequencies, and genic annotations for individual variants.
• Meta-analysis support: Supplies summary data suitable for comparative studies and meta-analyses of phenotype associations across populations.

Scientific Applications:

• Population genetics: Reference resource for studying allele frequency distributions and genetic diversity within Chinese populations.
• Comparative genomics: Enables comparative studies of variant frequencies between Chinese and global populations.
• Biomarker discovery: Supports identification of potential genetic biomarkers for disease susceptibility and complex traits.
• Phenotype association studies: Facilitates meta-analyses and association analyses of SNVs with traits such as height, BMI, maternal age, and twin pregnancy outcomes.
• Translational and clinical genomics: Provides baseline population variation data applicable to personalized medicine and translational research.

Methodology:

Variant dataset generated from low-coverage (0.06×–0.1×) whole-genome sequencing of 141,431 unrelated healthy individuals, producing 9.04 million SNVs with allele frequencies and genic annotations.