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@article{1552356,
author = {Skutkova, Helena and Vitek, Martin and Bezdíček, Matěj and Brhelová, Eva and Lengerová, Martina},
article_location = {AMSTERDAM},
article_number = {JUL 2019},
doi = {http://dx.doi.org/10.1016/j.jare.2019.01.005},
keywords = {DNA fingerprinting; Automated chip capillary electrophores; Genotyping; Band matching; Gel sample distortion; Pattern recognition},
language = {eng},
issn = {2090-1232},
journal = {JOURNAL OF ADVANCED RESEARCH},
title = {Advanced DNA fingerprint genotyping based on a model developed from real chip electrophoresis data},
url = {http://dx.doi.org/10.1016/j.jare.2019.01.005},
volume = {18},
year = {2019}
}
TY - JOUR
ID - 1552356
AU - Skutkova, Helena - Vitek, Martin - Bezdíček, Matěj - Brhelová, Eva - Lengerová, Martina
PY - 2019
TI - Advanced DNA fingerprint genotyping based on a model developed from real chip electrophoresis data
JF - JOURNAL OF ADVANCED RESEARCH
VL - 18
IS - JUL 2019
SP - 9-18
EP - 9-18
PB - ELSEVIER SCIENCE BV
SN - 20901232
KW - DNA fingerprinting
KW - Automated chip capillary electrophores
KW - Genotyping
KW - Band matching
KW - Gel sample distortion
KW - Pattern recognition
UR - http://dx.doi.org/10.1016/j.jare.2019.01.005
L2 - http://dx.doi.org/10.1016/j.jare.2019.01.005
N2 - Large-scale comparative studies of DNA fingerprints prefer automated chip capillary electrophoresis over conventional gel planar electrophoresis due to the higher precision of the digitalization process. However, the determination of band sizes is still limited by the device resolution and sizing accuracy. Band matching, therefore, remains the key step in DNA fingerprint analysis. Most current methods evaluate only the pairwise similarity of the samples, using heuristically determined constant thresholds to evaluate the maximum allowed band size deviation; unfortunately, that approach significantly reduces the ability to distinguish between closely related samples. This study presents a new approach based on global multiple alignments of bands of all samples, with an adaptive threshold derived from the detailed migration analysis of a large number of real samples. The proposed approach allows the accurate automated analysis of DNA fingerprint similarities for extensive epidemiological studies of bacterial strains, thereby helping to prevent the spread of dangerous microbial infections. (C) 2019 The Authors. Published by Elsevier B.V. on behalf of Cairo University.
ER -
SKUTKOVA, Helena, Martin VITEK, Matěj BEZDÍČEK, Eva BRHELOVÁ and Martina LENGEROVÁ. Advanced DNA fingerprint genotyping based on a model developed from real chip electrophoresis data. \textit{JOURNAL OF ADVANCED RESEARCH}. AMSTERDAM: ELSEVIER SCIENCE BV, 2019, vol.~18, JUL 2019, p.~9-18. ISSN~2090-1232. Available from: https://dx.doi.org/10.1016/j.jare.2019.01.005.
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