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A Tale of Two Genotypes: Consistency between Two High-Throughput Genotyping Centers
Multiple genome-wide scans involving sib-pairs or limited pedigrees have been extensively used for a wide number of complex genetic conditions. Comparing data from two or more scans, as well as combining data, require an understanding of the sources of genotyping errors and data discrepancies. We ha...
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Cold Spring Harbor Laboratory Press
2002
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| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC155285/ https://ncbi.nlm.nih.gov/pubmed/11875031 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1101/gr.211502 |
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pubmed-1552852003-05-22 A Tale of Two Genotypes: Consistency between Two High-Throughput Genotyping Centers Weeks, Daniel E. Conley, Yvette P. Ferrell, Robert E. Mah, Tammy S. Gorin, Michael B. Genome Res Letter Multiple genome-wide scans involving sib-pairs or limited pedigrees have been extensively used for a wide number of complex genetic conditions. Comparing data from two or more scans, as well as combining data, require an understanding of the sources of genotyping errors and data discrepancies. We have conducted two genome-wide scans for age-related maculopathy using the Center for Inherited Disease Research (CIDR) and the Mammalian Genotyping Service (MGS). Thirty individuals were typed in common, in order to allow for the alignment of alleles and comparison of the data sets. The analysis of these 8914 genotypes distributed over 321 markers in common demonstrated excellent agreement between these two laboratories, which have low rates of internal errors. Under the assumption that within each genotype, the smaller MGS allele should correspond to the smaller CIDR allele, the alleles align well between the two centers, with only a small fraction (less than 0.65%) of the aligned alleles showing large differences in sizes. However, since called allele sizes are integer “labels” which may not directly reflect the true underlying allele sizes, it is important to carefully prepare in advance if one wishes to merge data from different laboratories. In particular, it would not suffice to attempt to align alleles by typing only one or two controls in common. Fortunately, for the purposes of linkage analysis, one can avoid merging difficulties by simply carrying out linkage analyses using laboratory-specific allele labels and allele frequencies for each laboratory-specific subset of the data. Cold Spring Harbor Laboratory Press 2002-03 /pmc/articles/PMC155285/ /pubmed/11875031 http://dx.doi.org/10.1101/gr.211502 Text en Copyright © 2002, Cold Spring Harbor Laboratory Press |
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US National Library of Medicine |
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PubMed Central |
| language |
en |
| format |
Article |
| topic |
Letter |
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Letter Weeks, Daniel E. Conley, Yvette P. Ferrell, Robert E. Mah, Tammy S. Gorin, Michael B. A Tale of Two Genotypes: Consistency between Two High-Throughput Genotyping Centers |
| description |
Multiple genome-wide scans involving sib-pairs or limited pedigrees have been extensively used for a wide number of complex genetic conditions. Comparing data from two or more scans, as well as combining data, require an understanding of the sources of genotyping errors and data discrepancies. We have conducted two genome-wide scans for age-related maculopathy using the Center for Inherited Disease Research (CIDR) and the Mammalian Genotyping Service (MGS). Thirty individuals were typed in common, in order to allow for the alignment of alleles and comparison of the data sets. The analysis of these 8914 genotypes distributed over 321 markers in common demonstrated excellent agreement between these two laboratories, which have low rates of internal errors. Under the assumption that within each genotype, the smaller MGS allele should correspond to the smaller CIDR allele, the alleles align well between the two centers, with only a small fraction (less than 0.65%) of the aligned alleles showing large differences in sizes. However, since called allele sizes are integer “labels” which may not directly reflect the true underlying allele sizes, it is important to carefully prepare in advance if one wishes to merge data from different laboratories. In particular, it would not suffice to attempt to align alleles by typing only one or two controls in common. Fortunately, for the purposes of linkage analysis, one can avoid merging difficulties by simply carrying out linkage analyses using laboratory-specific allele labels and allele frequencies for each laboratory-specific subset of the data. |
| author |
Weeks, Daniel E. Conley, Yvette P. Ferrell, Robert E. Mah, Tammy S. Gorin, Michael B. |
| author_facet |
Weeks, Daniel E. Conley, Yvette P. Ferrell, Robert E. Mah, Tammy S. Gorin, Michael B. |
| author_sort |
Weeks, Daniel E. |
| title |
A Tale of Two Genotypes: Consistency between Two High-Throughput Genotyping Centers |
| title_short |
A Tale of Two Genotypes: Consistency between Two High-Throughput Genotyping Centers |
| title_full |
A Tale of Two Genotypes: Consistency between Two High-Throughput Genotyping Centers |
| title_fullStr |
A Tale of Two Genotypes: Consistency between Two High-Throughput Genotyping Centers |
| title_full_unstemmed |
A Tale of Two Genotypes: Consistency between Two High-Throughput Genotyping Centers |
| title_sort |
tale of two genotypes: consistency between two high-throughput genotyping centers |
| publisher |
Cold Spring Harbor Laboratory Press |
| publisher_facet |
Cold Spring Harbor Laboratory Press |
| publishDate |
2002 |
| url |
https://ncbi.nlm.nih.gov/pmc/articles/PMC155285/ https://ncbi.nlm.nih.gov/pubmed/11875031 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1101/gr.211502 |
| _version_ |
1759036745541746688 |