Tool for the analysis Mass Spectrometry (MS) data in the context of 
             immunopeptidomic analysis for the identification of hybrid 
             peptides and the predictions of binding affinity of all peptides 
             using 'netMHCpan' <doi:10.1093/nar/gkaa379> while providing a summary 
             of the netMHCpan output. 'RHybridFinder' (RHF) is destined for 
             researchers who are looking to analyze their MS data for the purpose 
             of identification of potential spliced peptides. This package, 
             developed mainly in base R, is based on the workflow published by 
             Faridi et al. in 2018 <doi:10.1126/sciimmunol.aar3947>.

Wrapper for 'Datamuse' API to find rhyming and other associated words.
    This includes words of similar meaning, spelling, or other related words. Learn
    more about the 'Datamuse' API here <https://www.datamuse.com/api/>.

Create and manipulate hypergraph objects. This early version of
    rhype allows for the output of matrices associated with the hypergraphs 
    themselves. It also uses these matrices to calculate hypergraph spectra and
    perform spectral comparison. Functionality coming soon includes calculation
    of hyperpaths and hypergraph centrality measures.

Randomization inference procedures for simple and complex randomized designs, including multi-armed trials, as described in Gerber and Green (2012, ISBN: 978-0393979954). Users formally describe their randomization procedure and test statistic. The randomization distribution of the test statistic under some null hypothesis is efficiently simulated.

Computes attributable effects based confidence interval, permutation test confidence interval, or asymptotic confidence interval for the average treatment effect on a binary outcome. Methods outlined in further detail in Rigdon and Hudgens (2015) <doi:10.1002/sim.6384>.

Radiomics image analysis toolbox for 2D and 3D radiological images. RIA supports DICOM, NIfTI,
             nrrd and npy (numpy array) file formats.
             RIA calculates first-order, gray level co-occurrence matrix, gray level run length matrix and
             geometry-based statistics. Almost all calculations are done using vectorized formulas to
             optimize run speeds. Calculation of several thousands of parameters only takes minutes
             on a single core of a conventional PC. Detailed methodology has been published: Kolossvary
             et al. Circ: Cardiovascular Imaging. 2017;10(12):e006843 <doi: 10.1161/CIRCIMAGING.117.006843>.