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.

Creating a custom mappings similarity matrix

In BioNumerics, character values can be mapped to categorical names according to predefined criteria (see this tutorial for more information about the use of mappings in BioNumerics). When character mappings are present, it becomes possible to define a custom mappings similarity matrix, which determines how similarities are calculated among the mappings. This can be useful when analyzing data sets like SNPs, VNTRs, SSRs, etc. In this tutorial the use of a custom mappings matrix is illustrated.

Importing non-numerical character data

This tutorial shows how to import non-numerical data in a BioNumerics database and link the data to a character type experiment. It illustrates the use of character mappings in BioNumerics. Character mappings in BioNumerics are used to map categorical names (e.g. Present/Absent, Yes/No, Susceptible/Intermediate/Resistant, etc.) to character values (e.g. 0 and 1) or a range of values to according to predefined criteria.