Abstract
We present Skan (Skeleton analysis), a Python library for the analysis of the skeleton structures of objects. It was inspired by the “analyse skeletons” plugin for the Fiji image analysis software, but its extensive Application Programming Interface (API) allows users to examine and manipulate any intermediate data structures produced during the analysis. Further, its use of common Python data structures such as SciPy sparse matrices and pandas data frames opens the results to analysis within the extensive ecosystem of scientific libraries available in Python. We demonstrate the validity of Skan’s measurements by comparing its output to the established Analyze Skeletons Fiji plugin, and, with a new scanning electron microscopy (SEM)-based method, we confirm that the malaria parasite Plasmodium falciparum remodels the host red blood cell cytoskeleton, increasing the average distance between spectrin-actin junctions.
Highlights
Skeletons are single-pixel thick representations of networks within an image, and have wide application to understanding the structural properties of objects
Prior studies have shown that infection by P. falciparum, the most deadly malaria-causing parasite, results in changes in the physical properties of the infected red blood cell, and that these changes are associated with an elongation of the spectrin skeleton branches in the inner red blood cells (RBCs) membrane skeleton (Shi et al, 2013; Dearnley et al, 2016; Nans, Mohandas & Stokes, 2011)
A coarse-grained molecular model suggested that this spectrin stretching could, in part, account for the deformability changes of the infected red blood cell (iRBC) (Dearnley et al, 2016), emphasizing the biological significance of the measurements
Summary
Skeletons are single-pixel thick representations of networks within an image, and have wide application to understanding the structural properties of objects. Skeletons have been used to model human poses, neuronal morphology, nanofibre structure, road networks, kidney development, and vascular networks, among others (Yim, Choyke & Summers, 2000; Sundar et al, 2003; Bas & Erdogmus, 2011; Yuan et al, 2009; MoralesNavarrete et al, 2015; Sambaer, Zatloukal & Kimmer, 2011). These applications include both 2D and 3D images, and often 3D images collected over time, underscoring the need for skeleton analysis software to support multiple imaging modalities and dimensionality. The source code is available at https://github.com/jni/skan (under a BSD 3-clause license), and we encourage readers
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