Rare variant association tests: burden tests (Bocher et al. 2019 <doi:10.1002/gepi.22210>) and the Sequence Kernel Association Test (Bocher et al. 2021 <doi:10.1038/s41431-020-00792-8>) in the whole genome; and genetic simulations.

Defines storage standard for Read, process, and analyze 
    intracranial electroencephalography and deep-brain stimulation in 'RAVE', 
    a reproducible framework for analysis and visualization of iEEG
    by Magnotti, Wang, and Beauchamp, (2020, 
    <doi:10.1016/j.neuroimage.2020.117341>). 
    Supports brain imaging data structure (BIDS) 
    <https://bids.neuroimaging.io> and native file structure to
    ingest signals from 'Matlab' data files, hierarchical data format 5 (HDF5), 
    European data format (EDF), BrainVision core data format (BVCDF), or 
    BlackRock Microsystem (NEV/NSx); process images in 
    Neuroimaging informatics technology initiative (NIfTI) and 
    'FreeSurfer' formats, providing brain imaging normalization to template 
    brain, facilitating 'threeBrain' package for comprehensive electrode 
    localization via 'YAEL' (your advanced electrode localizer) by Wang, 
    Magnotti, Zhang, and Beauchamp 
    (2023, <doi:10.1523/ENEURO.0328-23.2023>).

Provides access to the 'Ravelry' API <https://www.ravelry.com/groups/ravelry-api>. An R wrapper for pulling data from 'Ravelry.com', an organizational tool for crocheters, knitters, spinners, and weavers. You can retrieve pattern, yarn, author, and shop information by search or by a given id.

Provides an I/O interface between R data.frames and
    Raven DataFrames. Defines functions to both read and write DataFrame
    files, as well as serialize/deserialize data.frames/DataFrames.

Utilities for processing input and output files associated with the Raven Hydrological Modelling Framework. Includes various plotting functions, model diagnostics, reading output files into extensible time series format, and support for writing Raven input files. 
    The 'RavenR' package is also archived at Chlumsky et al. (2020) <doi:10.5281/zenodo.4248183>.
    The Raven Hydrologic Modelling Framework method can be referenced with Craig et al. (2020) <doi:10.1016/j.envsoft.2020.104728>.