Abstract
In biological experiments, phenotype evaluation is a common challenge. In a wide variety of applications, the phenotypic features of organisms have to be measured and statistically assessed. This is especially important as differences between wild-type and mutant or treated and untreated organisms are often very subtle. Here, we propose a set of digital image transformations that implement preprocessing, feature extraction and statistical analysis of image data that is typically generated in a biological experiment. Moreover we present AgED - Analysis given Experimental Data, a software toolkit that facilitates the process of phenotypic feature evaluation from digital image data in an automatized fashion. Suitable statistical analysis and visualization is performed and controlled via a Graphical User Interface. Furthermore, the use of open data structures allows for the convenient reuse of the acquired feature data with miscellaneous data-mining software and scientific workflow syste ms. The functionality of this software tool is demonstrated and validated by repeating a phytohormone response experiment carried out on the fresh water alga Coleochaete scutata. The results showed that the timely and automatic processing of digital image data aides the researcher and rationalizes the formerly lengthy and, at times, error prone data evaluation in spreadsheet documents. Furthermore, the software toolkit AgED establishes a comparable evaluation standard and provides ready-to-publish graphic export facilities.