Simple git client for R based on 'libgit2' <https://libgit2.org> with
    support for SSH and HTTPS remotes. All functions in 'gert' use basic R data 
    types (such as vectors and data-frames) for their arguments and return values.
    User credentials are shared with command line 'git' through the git-credential
    store and ssh keys stored on disk or ssh-agent.

Implements the gene-based segregation test(GESE) and the weighted GESE test for identifying genes with causal variants of large effects for family-based sequencing data. The methods are described in Qiao, D. Lange, C., Laird, N.M., Won, S., Hersh, C.P., et al. (2017). <DOI:10.1002/gepi.22037>. Gene-based segregation method for identifying rare variants for family-based sequencing studies. Genet Epidemiol 41(4):309-319. More details can be found at <http://scholar.harvard.edu/dqiao/gese>.

Reproducible, programmatic retrieval of datasets from the
    GESIS Data Archive.  The GESIS Data Archive <https://search.gesis.org>  
    makes available thousands of invaluable datasets, but researchers using
    these datasets are caught in a bind.  The archive's terms and conditions
    bar dissemination of downloaded datasets to third parties, but to ensure 
    that one's work can be reproduced, assessed, and built upon by others, one
    must provide access to the raw data one has employed.  The 'gesisdata'
    package cuts this knot by providing registered users with programmatic,
    reproducible access to GESIS datasets from within 'R'.

Promote access to the GESLA
    <https://gesla787883612.wordpress.com> (Global Extreme Sea Level
    Analysis) dataset, a higher-frequency sea-level record data from all
    over the world. It provides functions to download it entirely, or
    query subsets directly into R, without the need of downloading the
    full dataset. Also, it provides a built-in web-application, so that
    users can apply basic filters to select the data of interest,
    generating informative plots, and showing the selected sites.