Principal components analysis and discriminant analysis on a character data set

This video shows how to perform a principle components analysis and discriminant analysis on a character table in BioNumerics 7. To perform a PCA on fingerprint data, a band matching table needs to be created first.

Characters

A character is basically a name-value pair of which the value can be binary, multi-state or continuous. Because of this very broad definition, a wide variety of data can be analyzed as character types (= an array of characters). This includes morphological and biochemical features, commercial test panels (API®, Biolog®, Vitek®, etc.), antibiotics resistance profiles, fatty acid profiles, microarrays, SNP arrays, repeat numbers in MLVA, allelic profiles in MLST, etc.

Software major version: 
7.x
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