Article ; Online: Analysis of Genetic Ancestry from NGS Data Using EthSEQ.
Current protocols
2023 Volume 3, Issue 2, Page(s) e663
Abstract: Next-generation sequencing (NGS) is widely utilized both in translational cancer genomics studies and in the setting of precision medicine. Identification and stratification of an individual's ancestry is fundamental for the correct interpretation of ... ...
Abstract | Next-generation sequencing (NGS) is widely utilized both in translational cancer genomics studies and in the setting of precision medicine. Identification and stratification of an individual's ancestry is fundamental for the correct interpretation of genetic and genomic profiling. EthSEQ provides an easy and effective computational workflow to determine the ancestry of individuals, exploiting single nucleotide polymorphism genotypes computed from NGS data of whole-exome and targeted sequencing experiments. Genotypes are determined by EthSEQ from sequencing alignment files (BAM files) or can be provided as input in Variant Call Format (VCF) or CoreArray Genomic Data Structure (GDS) format. Ancestry is determined and assigned to individuals by EthSEQ exploiting a reference model and a standard or multi-step refinement approach based on Principal Component Analysis (PCA). A complete and detailed set of textual and graphical output files are generated by EthSEQ as result. EthSEQ is easy to use and can be integrated into any NGS-based processing pipeline also exploiting multi-core capabilities. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Perform ancestry analysis using a pre-computed reference model Alternate Protocol: Perform ancestry analysis using a user-specified GDS file as reference model Basic Protocol 2: Perform ancestry analysis using multi-step refinement Support Protocol 1: Create a reference model from multiple VCF genotype data files Support Protocol 2: Create VCF genotype data files from a BAM file. |
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MeSH term(s) | Humans ; Software ; Genomics/methods ; Genotype ; Information Storage and Retrieval ; High-Throughput Nucleotide Sequencing/methods |
Language | English |
Publishing date | 2023-01-27 |
Publishing country | United States |
Document type | Journal Article |
ISSN | 2691-1299 |
ISSN (online) | 2691-1299 |
DOI | 10.1002/cpz1.663 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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