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Enabling population assignment from cancer genomes with SNP2pop.
Qingyao Huang1,2, Michael Baudis3,4
1Institute of Molecular Life Science, University of Zurich, Winterthurerstrasse 190, 8057, Zurich, Switzerland.
Scientific Reports
|March 18, 2020
Summary
This study introduces SNP2pop, a bioinformatics tool for accurate ancestry estimation in cancer genomes, even with somatic mutations. It enables better understanding of cancer disparities across populations.
Area of Science:
- Genomics
- Cancer Biology
- Population Genetics
Background:
- Cancer incidence, treatment, and prognosis vary significantly across geographic populations.
- Understanding these variations requires disentangling genetic, environmental, and lifestyle factors.
- Genomic data is crucial for accurate ancestry estimation, overcoming limitations of self-reported or inferred metadata.
Purpose of the Study:
- To develop and validate a bioinformatics tool for assigning population groups from genomic data in both normal and cancer genomes.
- To assess the accuracy of ancestry estimation in cancer genomes with high somatic mutation loads.
- To enable population structure analysis in cancer genomics research.
Main Methods:
- Development of the SNP2pop bioinformatics tool for ancestry assignment.
- Application of the tool to both germline and cancer genomes.
- Comparison of SNP2pop results with self-reported ethnicity data.
Main Results:
- SNP2pop achieves high consistency between germline and cancer data for ancestry assignment (97% for 5 groups, 92% for 26 groups).
- The tool demonstrates robustness despite substantial somatic mutations in cancer genomes.
- Matching rates with self-reported metadata range from 88-92%, with discrepancies often due to label interpretation.
Conclusions:
- SNP2pop accurately estimates population structure from genomic data, including challenging cancer samples.
- The tool facilitates research into the influence of genetic background on cancer biology.
- SNP2pop supports investigations into the interplay of ethnicity, environment, and somatic mutations in cancer.
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