Nuclear Morphology Analysis 2.0.0: Improved image analysis software for measuring nuclear shape

We generally imagine cells to have spherical or ellipsoidal nuclei, but many cell types are far more interesting, with great variation in nuclear shapes and sizes (Skinner & Johnson, 2017). Measuring and comparing shapes of cell nuclei in esoteric cell types such as sperm has traditionally been performed by manual assessment. Semi-automated approaches have been developed: geometric morphometric methods allow distinction of subtle phenotypic differences, as in the software MorphoJ (Klingenberg, 2011), but still require manual landmark annotation in each image (e.g. Varea-Sánchez et al. (2016)). Decomposing nuclear outlinesinto elliptic fourier descriptors is simpler and allows high-throughput analysis, as in the SHAPE software (Iwata & Ukai, 2002), but does not describe sharp corners well (e.g. Ostermeier et al. (2001), Mashiko et al. (2017)). Consequently, these methods have problems in reproducibility, scalability, or ease of use for biologists. At the other end of the spectrum are open source tools designed for high-throughput image processing such as CellProfiler (Stirling et al., 2021), with clear documentation and tutorials, but which do not have the ability to natively perform specialised morphometric analysis. Nuclear Morphology Analysis is a tool for measuring and comparing the shapes of cell nuclei. The software uses a modified Zahn-Roskies transformation (Zahn & Roskies, 1972) to convert the outlines of detected objects into linear profiles, with rules to identify landmarks of interest from these profiles. This approach allows high-throughput and reproducible analyses, detecting subtle variation in nuclear shape that is beyond the scope of manual assessment. This article outlines improvements made for Nuclear Morphology Analysis v2.0.0, available at https://bitbucket.org/bmskinner/nuclear_morphology/wiki/Home.