Novel algorithm for automated genotyping of microsatellites
Author(s) -
T. Matsumoto,
Wataru Yukawa,
Yasuyuki Nozaki,
Ryo Nakashige,
Minori Shinya,
Satoshi Makino,
Masaru Yagura,
Tomoki Ikuta,
Tadashi Imanishi,
Hidetoshi Inoko,
Gen Tamiya,
Takashi Gojobori
Publication year - 2004
Publication title -
nucleic acids research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.008
H-Index - 537
eISSN - 1362-4954
pISSN - 0305-1048
DOI - 10.1093/nar/gkh946
Subject(s) - genotyping , microsatellite , biology , genetics , computational biology , allele , polymerase chain reaction , genotype , gene
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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