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.
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.
Demonstration database containing SNP data for 37 entries. A set of 10 SNPs were screened. The screening was performed on diploid organisms, resulting in 10 possible states (4 homozygous and 6 heterozygous states).
Note that the downloaded database backup file (.bnbk) can be restored via the Restore database... functionality in the BIONUMERICS startup screen.