UT-AIM250
"UT-AIM250" is an R software tool to address the challenges of accurately determining genetic admixture proportions in populations, particularly in the context of health disparities among Hispanics in the U.S. due to their diverse genetic ancestry, primarily from Europeans and American Indians. This diversity impacts cancer susceptibility studies, where the genetic admixture may introduce biases, especially in liver cancer incidence rates among different populations.
Unique Approach to Ancestry Inference:
UT-AIM250 introduces a novel Ancestry Informative Marker (AIM) panel designed for inferring genetic admixture from three major continental populations: African (AFR), European (EUR), and East Asian (EAS). Unlike conventional AIMs in non-coding regions and not covered by Whole Exome Sequencing (WES) protocols, UT-AIM250 focuses on evolutionarily conserved exonic regions. This approach enables accurately determining a patient's admixture proportions using WES data, which is more commonly available in translational research and clinical settings.
Topic
Exome sequencing;Genomics;DNA polymorphism;Mapping;Oncology
Detail
Operation: Genotyping;Sequence trimming;Essential dynamics;Linkage disequilibrium calculation
Software interface: Command-line interface
Language: R
License: Not stated
Cost: Free of charge
Version name: -
Credit: NCI Cancer Center Shared Resources, NIH, CPRIT, San Antonio Life Science Institute, Clayton Foundation, NIH Shared Instrument, and Greehey CCRI Donald G McEwen Memorial Summer Undergraduate Research Program.
Input: -
Output: -
Contact: Yidong Chen cheny8@uthscsa.edu
Collection: -
Maturity: -
Publications
- An ancestry informative marker panel design for individual ancestry estimation of Hispanic population using whole exome sequencing data.
- Wang LJ, et al. An ancestry informative marker panel design for individual ancestry estimation of Hispanic population using whole exome sequencing data. An ancestry informative marker panel design for individual ancestry estimation of Hispanic population using whole exome sequencing data. 2019; 20:1007. doi: 10.1186/s12864-019-6333-6
- https://doi.org/10.1186/S12864-019-6333-6
- PMID: 31888480
- PMC: PMC6936141
Download and documentation
Documentation: --
Home page: https://github.com/chenlabgccri/UT-AIM250
Links: https://github.com/chenlabgccri/UT-AIM250/tree/master/Examples
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