Zusammenfassung
Deducing common properties or degrees of phylogenetic relationship by analyzing a grouping or clustering of sequence sets is a frequently used technique in computational biology. If interpreted by means of visual inspection, the conclusions depend for many of these applications on meaningful names for the input data. In accordance with the aim of the analysis, the sequences should be provided ...
Zusammenfassung
Deducing common properties or degrees of phylogenetic relationship by analyzing a grouping or clustering of sequence sets is a frequently used technique in computational biology. If interpreted by means of visual inspection, the conclusions depend for many of these applications on meaningful names for the input data. In accordance with the aim of the analysis, the sequences should be provided with names indicating the function of the genes or gene-products, the phylogenetic position or other properties characterizing the contributing species. However, sequences extracted from databases are most often annotated with identifiers which only implicitly contain the desired information. To solve this problem, we have designed and implemented a tool named Key2Ann, which replaces in multiple fasta files the database keys with short terms indicating the taxonomic position or other features like the gene name or the EC-number. In addition, properties like habitat, growth temperature or the degree of pathogenicity can be coded for microbial species. To allow for highest flexibility, the user can control the composition of the names by means of command line parameters. Key2Ann is written in Java and can be downloaded via http://www-bioinf.uni-regensburg.de/downl/Key2Ann.zip. We demonstrate the usage of Key2Ann by discussing three typical examples of phylogenetic analysis.
Altmetric