TISMorph: A tool to quantify texture, irregularity andspreading of single cells

Abstract

A number of recent studies have shown that cell shape and cytoskeletal texture can be used as sensitive readouts of the physiological state of the cell. However, utilization of this information requires the development of quantitative measures that can describe relevant aspects of cell shape. In this paper we develop a toolbox, TISMorph, to calculate set of quantitative measures to address this need. Some of the measures introduced here are used previously and others are new and have desirable properties for shape and texture quantification of cells. These measures, broadly classifiable into the categories of textural, spreading and irregularity measures, are tested by using them to discriminate between osteosarcoma cell lines treated with different cytoskeletal drugs. We find that even though specific classification tasks often rely on a few measures, these are not the same between all classification tasks, thus requiring the use of the entire suite of measures for classification and discrimination. We provide detailed descriptions of the measures, well as TISMorph package to implement them. Image based quantitative analysis has the potential to become a new field of biological data (\"image-omics\"), providing quantitative insight into cellular processes.