ArticleNucleic acids research2004
Novel algorithm for automated genotyping of microsatellites.
Article in Nucleic acids research, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Cross-amplification of ungulate microsatellite markers in the endemic Indian antelope or blackbuck (Antilope cervicapra) for population monitoring and conservation genetics studies in south Asia.Molecular biology reports · 2021Article
- Panel of polymorphic heterologous microsatellite loci to genotype critically endangered Bengal tiger: a pilot study.SpringerPlus · 2014Article
- Electrophoretic techniques applied to the detection and analysis of the human microsatellite DG10s478.Journal of biomolecular techniques : JBT · 2007Article
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Authors and funding
12 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Microsatellites or short tandem repeats (STRs) are abundant in the human genome with easily assayed polymorphisms, providing powerful genetic tools for mapping both Mendelian and complex traits. Microsatellite genotyping requires detection of the products of polymerase chain reaction (PCR) amplification by electrophoresis, and analysis of the peak data for discrimination of the true allele. A high-throughput genotyping approach requires computer-based automation at both the detection and analysis phases. In order to achieve this, complicated peak patterns from individual alleles must be interpreted in order to assign alleles. Previous methods consider limited types of noise peaks and cannot provide enough accuracy. By pattern recognition of various types of noise peaks, such as stutter peaks and additional peaks, we have achieved an overall average accuracy of 94% for allele calling in our actual data. Our algorithm is crucial for a high-throughput genotyping system for microsatellite markers by reducing manual editing and human errors.
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