Functions for processing, analysis and visualization of Hydrogen Deuterium eXchange monitored by 
             Mass Spectrometry experiments (HDX-MS) (<doi:10.1093/bioinformatics/btaa587>). 'HaDeX' introduces a new 
             standardized and reproducible workflow for the analysis of the HDX-MS data, including novel 
             uncertainty intervals. Additionally, it covers data exploration, quality control and generation of 
             publication-quality figures. All functionalities are also available in the in-built 'Shiny' app.

Hadamard matrix based statistical designs are of immense importance as the resultant designs carry various desirable characterizing properties. Constructing Partially Balanced Incomplete Block Designs (PBIBds) using Kronecker product of incidence matrices of Balanced Incomplete Block (BIB) and Partially Balanced Incomplete Block (PBIB) designs is much evident from literature. Here, we have constructed Incomplete Block Designs (IBDs) based on Hadamard matrices and Kronecker product of Hadamard matrices.

Analysis of plant pathogen pathotype survey data.  Functions
    provided calculate distribution of susceptibilities, distribution of
    complexities with statistics, pathotype frequency distribution, as
    well as diversity indices for pathotypes.  This package is meant to be
    a direct replacement for Herrmann, Löwer and Schachtel's (1999)
    <doi:10.1046/j.1365-3059.1999.00325.x> Habgood-Gilmour Spreadsheet,
    'HaGiS', previously used for pathotype analysis.

Haplotype-aware Hidden Markov Model for RNA (HaHMMR) is a method for detecting copy number variations (CNVs) from bulk RNA-seq data. Additional examples, documentations, and details on the method are available at <https://github.com/kharchenkolab/hahmmr/>.

Initializes a class that obtains API credentials and provides
    a method to use those credentials to make GET requests to the 'Hakai'
    API server. Usage instructions are documented at
    <https://hakaiinstitute.github.io/hakai-api/>.