Description and critical appraisal of principal components analysis (PCA) methodology applied to pulsed-field gel electrophoresis profiles of methicillin-resistant Staphylococcus aureus isolates

被引:5
作者
Caddick, JM
Hilton, AC [1 ]
Armstrong, RA
Lambert, PA
Worthington, T
Elliott, TSJ
机构
[1] Aston Univ, Birmingham B4 7ET, W Midlands, England
[2] Univ Hosp Birmingham NHS Trust, Birmingham, W Midlands, England
关键词
cluster analysis; Staphylococcus aureus; principal components analysis; pulsed-field gel electrophoresis;
D O I
10.1016/j.mimet.2005.06.017
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Principal components analysis (PCA) has been described for over 50 years, however, it is rarely applied to the analysis of epidemiological data. In this study PCA was critically appraised in its ability to reveal relationships between pulsed-field gel electrophoresis (PFGE) profiles of methicillin-resistant Staphylococcus aureus (MRSA) in comparison to the more commonly employed Cluster analysis and representation by dendrograms. The PFGE type following Sinal chromosomal digest was determined for 44 multidrug-resistant hospital-acquired methicillin-resistant S. aurens (MR-HA-MRSA) isolates, two multidrug-resistant community-acquired MRSA (MR-CA-MRSA), 50 hospital-acquired MRSA (HA-MRSA) isolates (from the University Hospital Birmingham, NHS Trust, UK) and 34 community-acquired MRSA (CA-MRSA) isolates (from general practitioners in Birmingham, UK). Strain relatedness was determined using Dice band-matching with UPGMA clustering and PCA. The results indicated that PCA revealed relationships between MRSA strains, which were more strongly correlated with known epidemiology, most likely because, unlike cluster analysis, PCA does not have the constraint of generating a hierarchic classification. In addition, PCA provides the opportunity for further analysis to identify key polymorphic bands within complex genotypic profiles, which is not always possible with dendrograms. Here we provide a detailed description of a PCA method for the analysis of PFGE profiles to complement further the epidemiological study of infectious disease. (c) 2005 Elsevier B.V. All rights reserved.
引用
收藏
页码:87 / 95
页数:9
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