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DC Field | Value | Language |
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dc.contributor.author | Martin, Alicia R. | - |
dc.contributor.author | Atkinson, Elizabeth G. | - |
dc.contributor.author | Ashaba, Fred K. | - |
dc.contributor.author | Atwoli, Lukoye | - |
dc.contributor.author | Gichuru, Stella | - |
dc.contributor.author | Injera, Wilfred E. | - |
dc.contributor.author | Kariuki, Symon M. | - |
dc.contributor.author | Roxanne, James | - |
dc.contributor.author | Kigen, Gabriel | - |
dc.contributor.author | Dodge, Sheila | - |
dc.contributor.author | Stevenson, Anne | - |
dc.date.accessioned | 2020-10-14T08:39:23Z | - |
dc.date.available | 2020-10-14T08:39:23Z | - |
dc.date.issued | 2020 | - |
dc.identifier.uri | https://doi.org/10.1101/2020.04.27.064832 | - |
dc.identifier.uri | http://ir.mu.ac.ke:8080/jspui/handle/123456789/3562 | - |
dc.description.abstract | Background Genetic studies of biomedical phenotypes in underrepresented populations identify disproportionate numbers of novel associations. However, current genomics infrastructure--including most genotyping arrays and sequenced reference panels--best serves populations of European descent. A critical step for facilitating genetic studies in underrepresented populations is to ensure that genetic technologies accurately capture variation in all populations. Here, we quantify the accuracy of low-coverage sequencing in diverse African populations. Results We sequenced the whole genomes of 91 individuals to high-coverage (≥20X) from the Neuropsychiatric Genetics of African Population-Psychosis (NeuroGAP-Psychosis) study, in which participants were recruited from Ethiopia, Kenya, South Africa, and Uganda. We empirically tested two data generation strategies, GWAS arrays versus low-coverage sequencing, by calculating the concordance of imputed variants from these technologies with those from deep whole genome sequencing data. We show that low-coverage sequencing at a depth of ≥4X captures variants of all frequencies more accurately than all commonly used GWAS arrays investigated and at a comparable cost. Lower depths of sequencing (0.5-1X) performed comparable to commonly used low-density GWAS arrays. Low-coverage sequencing is also sensitive to novel variation, with 4X sequencing detecting 45% of singletons and 95% of common variants identified in high-coverage African whole genomes. Conclusion These results indicate that low-coverage sequencing approaches surmount the problems induced by the ascertainment of common genotyping arrays, including those that capture variation most common in Europeans and Africans. Low-coverage sequencing effectively identifies novel variation (particularly in underrepresented populations), and presents opportunities to enhance variant discovery at a similar cost to traditional approaches. | en_US |
dc.language.iso | en | en_US |
dc.publisher | bioRxiv | en_US |
dc.subject | Low-coverage sequencing | en_US |
dc.subject | Whole genome sequencing | en_US |
dc.subject | Study design | en_US |
dc.title | Low-coverage sequencing cost-effectively detects knownand novel variation in underrepresented populations | en_US |
dc.type | Article | en_US |
Appears in Collections: | School of Medicine |
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