Genomic regions processing using open-source command line tools such as 'BEDTools', 'BEDOPS' and 'Tabix'. 
  These tools offer scalable and efficient utilities to perform genome arithmetic e.g indexing, formatting and merging.
  bedr API enhances access to these tools as well as offers additional utilities for genomic regions processing.

Flags and checks occurrence data that are in Darwin Core
    format.  The package includes generic functions and data as well as
    some that are specific to bees. This package is meant to build upon
    and be complimentary to other excellent occurrence cleaning packages,
    including 'bdc' and 'CoordinateCleaner'.  This package uses datasets
    from several sources and particularly from the Discover Life Website,
    created by Ascher and Pickering (2020).  For further information,
    please see the original publication and package website.  Publication
    - Dorey et al. (2023) <doi:10.1101/2023.06.30.547152> and package
    website - Dorey et al. (2023) <https://github.com/jbdorey/BeeBDC>.

Tools to calibrate, validate, and make predictions with the
    General Unified Threshold model of Survival adapted for Bee species. The
    model is presented in the publication from Baas, J., Goussen, B., Miles, M.,
    Preuss, T.G., Roessing, I. (2022) <doi:10.1002/etc.5423> and is based on the GUTS framework
    Jager, T., Albert, C., Preuss, T.G. and Ashauer, R. (2011) <doi:10.1021/es103092a>.
    The authors are grateful to Bayer A.G. for its financial support.

The main function of this package is beep(), with the purpose to
    make it easy to play notification sounds on whatever platform you are on.
    It is intended to be useful, for example, if you are running a long analysis
    in the background and want to know when it is ready.

The bee swarm plot is a one-dimensional scatter plot like
    "stripchart", but with closely-packed, non-overlapping points.

Facilitates many of the analyses performed in studies of
    behavioral economic demand. The package supports commonly-used options for
		modeling operant demand including (1) data screening proposed by Stein,
		Koffarnus, Snider, Quisenberry, & Bickel (2015; <doi:10.1037/pha0000020>),
		(2) fitting models of demand such as linear (Hursh, Raslear, Bauman,
		& Black, 1989, <doi:10.1007/978-94-009-2470-3_22>), exponential	(Hursh & Silberberg, 2008,
		<doi:10.1037/0033-295X.115.1.186>) and modified exponential (Koffarnus,
		Franck, Stein, & Bickel, 2015, <doi:10.1037/pha0000045>), and (3) calculating
		numerous measures	relevant to applied behavioral economists (Intensity,
		Pmax, Omax). Also	supports plotting and comparing data.