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heiDATA is an institutional repository for research data of Heidelberg University. It is managed by the Competence Centre for Research Data, a joint institution of the University Library and the Computing Centre. If you are interested in publishing your data here, please see our author instructions and get in touch with us.
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Oct 15, 2018 - Statistical Genetics
Kabisch, Maria ; Hamann, Ute; Lorenzo Bermejo, Justo, 2018, "Imputation of Missing Genotypes within LD-Blocks Relying on the Basic Coalescent and Beyond [Source Code]", https://doi.org/10.11588/data/X9UEHB, heiDATA, V1
Background Genotypes not directly measured in genetic studies are often imputed to improve statistical power and to increase mapping resolution. The accuracy of standard imputation techniques strongly depends on the similarity of linkage disequilibrium (LD) patterns in the study...
application/x-sas-syntax - 17.8 KB - MD5: 1f43b2e6248d3962c00c8ca6afd02e95
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Oct 15, 2018 - Statistical Genetics
Peil, Barbara; Kabisch, Maria; Fischer, Christine; Hamann, Ute; Lorenzo Bermejo, Justo, 2018, "Tailored Selection of Study Individuals to be Sequenced in Order to Improve the Accuracy of Genotype Imputation [Source Code]", https://doi.org/10.11588/data/TT4VM3, heiDATA, V1
The addition of sequence data from own‐study individuals to genotypes from external data repositories, for example, the HapMap, has been shown to improve the accuracy of imputed genotypes. Early approaches for reference panel selection favored individuals who best reflect recombi...
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