A modular package for measuring disparity (multidimensional space occupancy). Disparity can be calculated from any matrix defining a multidimensional space. The package provides a set of implemented metrics to measure properties of the space and allows users to provide and test their own metrics. The package also provides functions for looking at disparity in a serial way (e.g. disparity through time) or per groups as well as visualising the results. Finally, this package provides several statistical tests for disparity analysis.

Similarity of dissolution profiles is assessed using the
    similarity factor f2 according to the EMA guideline (European
    Medicines Agency 2010) "On the investigation of bioequivalence".
    Dissolution profiles are regarded as similar if the f2 value is
    between 50 and 100. For the applicability of the similarity factor f2,
    the variability between profiles needs to be within certain limits.
    Often, this constraint is violated. One possibility in this situation
    is to resample the measured profiles in order to obtain a bootstrap
    estimate of f2 (Shah et al. (1998) <doi:10.1023/A:1011976615750>).
    Other alternatives are the model-independent non-parametric
    multivariate confidence region (MCR) procedure (Tsong et al. (1996)
    <doi:10.1177/009286159603000427>) or the T2-test for equivalence
    procedure (Hoffelder (2016)
    <https://www.ecv.de/suse_item.php?suseId=Z|pi|8430>). Functions for
    estimation of f1, f2, bootstrap f2, MCR / T2-test for equivalence
    procedure are implemented.

Set of tools for molecular probes selection and design of a microarray, e.g. the assessment of physical and chemical properties, blast performance, selection according to sensitivity and selectivity. Methods used in package are described in: Lorenz R., Stephan H.B., Höner zu Siederdissen C. et al. (2011) <doi:10.1186/1748-7188-6-26>; Camacho C., Coulouris G., Avagyan V. et al. (2009) <doi:10.1186/1471-2105-10-421>.

Calculate multiple or pairwise dissimilarity for orders q = 0-N 
    (CqN; Chao et al. 2008 <doi:10/fcvn63>) for a set of species assemblages or 
    interaction networks.