gplots, quantreg, sfa, KernSmooth, lpSolve, ggplot2,
doParallel, foreach, iterators

Performs a Necessary Condition Analysis (NCA). (Dul, J. 2016. Necessary Condition Analysis (NCA). ''Logic and Methodology of 'Necessary but not Sufficient' causality." Organizational Research Methods 19(1), 10-52,
<https://journals.sagepub.com/doi/full/10.1177/1094428115584005>).
NCA identifies necessary (but not sufficient) conditions in datasets, where x causes (e.g. precedes) y. Instead of drawing a regression line ''through the middle of the data'' in an xy-plot, NCA draws the ceiling line. The ceiling line y = f(x) separates the area with observations from the area without observations.
(Nearly) all observations are below the ceiling line: y <= f(x). The empty zone is in the upper left hand corner of the xy-plot (with the convention that the x-axis is ''horizontal'' and the y-axis is ''vertical'' and that values increase ''upwards'' and ''to the right''). The ceiling line is a (piecewise) linear non-decreasing line: a linear step function or a straight line. It indicates which level of x (e.g. an effort or input) is necessary but not sufficient for a (desired) level of y (e.g. good performance or output). A quick start guide for using this package can be found here: <https://repub.eur.nl/pub/78323/> or <https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2624981>.
gplots, quantreg, sfa, KernSmooth, lpSolve, ggplot2,
doParallel, foreach, iterators, plotly

gplots, quantreg, KernSmooth, lpSolve, ggplot2, doParallel,
foreach, iterators, plotly

NCBI2R-An R package to navigate and annotate genes and SNPs
NCBI2R is a R package that annotates lists of SNPs and/or
genes, with current information from NCBI, including LD
information. Functions are provided that with one command will
provide annotation of the results from genome wide association
studies to provide a broader context of their meaning. Other
functions enable comparisons between a user's GWA results, and
candidate snp/gene lists that are created from keywords, such
as specific diseases, phenotypes or gene ontology terms.
Commands are simple to follow and designed to work with R
objects to integrate into existing workflows. The output
produces text fields and weblinks to more information for items
such as: gene descriptions, nucleotide positions, OMIM,
pathways, phenotypes, and lists of interacting and neighboring
genes. Annotation can then be used in R for further analysis,
or the objects can be customized for use in spreadsheet
programs or web browsers. The NCBI2R package was designed to
allow those performing genome analysis to produce output that
could easily be understood by a person not familiar with R.
Please see the new website at http://NCBI2R.wordpress.com for
more information. The internet is required for almost all of
these functions.