AUTOMATIC CLASSIFICATION OF STAPHYLOCOCCI BY PRINCIPAL-COMPONENT ANALYSIS AND A GRADIENT METHOD

J Bacteriol. 1965 May;89(5):1393-401. doi: 10.1128/jb.89.5.1393-1401.1965.

Abstract

Hill, L. R. (Università Statale, Milano, Italy), L. G. Silvestri, P. Ihm, G. Farchi, and P. Lanciani. Automatic classification of staphylococci by principal-component analysis and a gradient method. J. Bacteriol. 89:1393-1401. 1965.-Forty-nine strains from the species Staphylococcus aureus, S. saprophyticus, S. lactis, S. afermentans, and S. roseus were submitted to different taxometric analyses; clustering was performed by single linkage, by the unweighted pair group method, and by principal-component analysis followed by a gradient method. Results were substantially the same with all methods. All S. aureus clustered together, sharply separated from S. roseus and S. afermentans; S. lactis and S. saprophyticus fell between, with the latter nearer to S. aureus. The main purpose of this study was to introduce a new taxometric technique, based on principal-component analysis followed by a gradient method, and to compare it with some other methods in current use. Advantages of the new method are complete automation and therefore greater objectivity, execution of the clustering in a space of reduced dimensions in which different characters have different weights, easy recognition of taxonomically important characters, and opportunity for representing clusters in three-dimensional models; the principal disadvantage is the need for large computer facilities.

MeSH terms

  • Classification*
  • Cluster Analysis*
  • Electronic Data Processing*
  • Italy
  • Models, Theoretical*
  • Research*
  • Staphylococcal Infections*
  • Staphylococcus aureus*
  • Staphylococcus*