Efficiency and power as a function of sequence coverage, SNP array density, and imputation.
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Abstract | High coverage whole genome sequencing provides near complete information about genetic variation. However, other technologies can be more efficient in some settings by (a) reducing redundant coverage within samples and (b) exploiting patterns of genetic variation across samples. To characterize as many samples as possible, many genetic studies therefore employ lower coverage sequencing or SNP array genotyping coupled to statistical imputation. To compare these approaches individually and in conjunction, we developed a statistical framework to estimate genotypes jointly from sequence reads, array intensities, and imputation. In European samples, we find similar sensitivity (89%) and specificity (99.6%) from imputation with either 1× sequencing or 1 M SNP arrays. Sensitivity is increased, particularly for low-frequency polymorphisms (MAF |
Year of Publication | 2012
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Journal | PLoS Comput Biol
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Volume | 8
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Issue | 7
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Pages | e1002604
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Date Published | 2012
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ISSN | 1553-7358
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DOI | 10.1371/journal.pcbi.1002604
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PubMed ID | 22807667
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PubMed Central ID | PMC3395607
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Grant list | T32 GM007748 / GM / NIGMS NIH HHS / United States
U01 HG005208 / HG / NHGRI NIH HHS / United States
5-T32-GM007748-33 / GM / NIGMS NIH HHS / United States
U01HG005208 / HG / NHGRI NIH HHS / United States
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