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Algorithm for automatic genotype calling of single nucleotide polymorphisms using the full course of TaqMan real-time data
Single nucleotide polymorphisms (SNPs) are often determined using TaqMan real-time PCR assays (Applied Biosystems) and commercial software that assigns genotypes based on reporter probe signals at the end of amplification. Limitations to the large-scale application of this approach include the need...
Autores principales: | , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2006
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1440877/ https://www.ncbi.nlm.nih.gov/pubmed/16617143 http://dx.doi.org/10.1093/nar/gkl185 |
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author | Callegaro, A. Spinelli, R. Beltrame, L. Bicciato, S. Caristina, L. Censuales, S. De Bellis, G. Battaglia, C. |
author_facet | Callegaro, A. Spinelli, R. Beltrame, L. Bicciato, S. Caristina, L. Censuales, S. De Bellis, G. Battaglia, C. |
author_sort | Callegaro, A. |
collection | PubMed |
description | Single nucleotide polymorphisms (SNPs) are often determined using TaqMan real-time PCR assays (Applied Biosystems) and commercial software that assigns genotypes based on reporter probe signals at the end of amplification. Limitations to the large-scale application of this approach include the need for positive controls or operator intervention to set signal thresholds when one allele is rare. In the interest of optimizing real-time PCR genotyping, we developed an algorithm for automatic genotype calling based on the full course of real-time PCR data. Best cycle genotyping algorithm (BCGA), written in the open source language R, is based on the assumptions that classification depends on the time (cycle) of amplification and that it is possible to identify a best discriminating cycle for each SNP assay. The algorithm is unique in that it classifies samples according to the behavior of blanks (no DNA samples), which cluster with heterozygous samples. This method of classification eliminates the need for positive controls and permits accurate genotyping even in the absence of a genotype class, for example when one allele is rare. Here, we describe the algorithm and test its validity, compared to the standard end-point method and to DNA sequencing. |
format | Text |
id | pubmed-1440877 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2006 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-14408772006-05-04 Algorithm for automatic genotype calling of single nucleotide polymorphisms using the full course of TaqMan real-time data Callegaro, A. Spinelli, R. Beltrame, L. Bicciato, S. Caristina, L. Censuales, S. De Bellis, G. Battaglia, C. Nucleic Acids Res Methods Online Single nucleotide polymorphisms (SNPs) are often determined using TaqMan real-time PCR assays (Applied Biosystems) and commercial software that assigns genotypes based on reporter probe signals at the end of amplification. Limitations to the large-scale application of this approach include the need for positive controls or operator intervention to set signal thresholds when one allele is rare. In the interest of optimizing real-time PCR genotyping, we developed an algorithm for automatic genotype calling based on the full course of real-time PCR data. Best cycle genotyping algorithm (BCGA), written in the open source language R, is based on the assumptions that classification depends on the time (cycle) of amplification and that it is possible to identify a best discriminating cycle for each SNP assay. The algorithm is unique in that it classifies samples according to the behavior of blanks (no DNA samples), which cluster with heterozygous samples. This method of classification eliminates the need for positive controls and permits accurate genotyping even in the absence of a genotype class, for example when one allele is rare. Here, we describe the algorithm and test its validity, compared to the standard end-point method and to DNA sequencing. Oxford University Press 2006 2006-04-14 /pmc/articles/PMC1440877/ /pubmed/16617143 http://dx.doi.org/10.1093/nar/gkl185 Text en © The Author 2006. Published by Oxford University Press. All rights reserved |
spellingShingle | Methods Online Callegaro, A. Spinelli, R. Beltrame, L. Bicciato, S. Caristina, L. Censuales, S. De Bellis, G. Battaglia, C. Algorithm for automatic genotype calling of single nucleotide polymorphisms using the full course of TaqMan real-time data |
title | Algorithm for automatic genotype calling of single nucleotide polymorphisms using the full course of TaqMan real-time data |
title_full | Algorithm for automatic genotype calling of single nucleotide polymorphisms using the full course of TaqMan real-time data |
title_fullStr | Algorithm for automatic genotype calling of single nucleotide polymorphisms using the full course of TaqMan real-time data |
title_full_unstemmed | Algorithm for automatic genotype calling of single nucleotide polymorphisms using the full course of TaqMan real-time data |
title_short | Algorithm for automatic genotype calling of single nucleotide polymorphisms using the full course of TaqMan real-time data |
title_sort | algorithm for automatic genotype calling of single nucleotide polymorphisms using the full course of taqman real-time data |
topic | Methods Online |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1440877/ https://www.ncbi.nlm.nih.gov/pubmed/16617143 http://dx.doi.org/10.1093/nar/gkl185 |
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