Permutation Based QQ Plot and Inflation Factor Estimation
Provides users the necessary utility functions to generate permutation-based QQ plots and also estimate inflation factor based on the empirical NULL distribution. While it has general utility, it is particularly helpful when the skewness of the Fisher's Exact test in sparse data situations with imbalanced case-control sample sizes renders the reliance on the uniform chi-square expected distribution inappropriate.

person(given = "Juan", family = "Claramunt Gonzalez", role = c("aut", "cre","cph"), email
= "j.claramunt.gonzalez@fsw.leidenuniv.nl")
This function performs QR factorization without pivoting to a numeric matrix. It is based on Anderson. E. and ten others (1999) "LAPACK Users' Guide". Third Edition. SIAM.

This function performs QR factorization without pivoting to a real or complex matrix. It is based on Anderson. E. and ten others (1999) "LAPACK Users' Guide". Third Edition. SIAM.

A 'Shiny' Gadget for Interactive 'QRA' Visualizations
Upload raster data and easily create interactive quantitative risk analysis 'QRA' visualizations. Select
from numerous color palettes, base-maps, and different configurations.
htmlwidgets, leaflet, magrittr, miniUI, raster, scales, shiny,
sp

Quadratically Regularized Functional Canonical Correlation
Analysis
Conduct quadratically regularized functional canonical correlation analysis.  The details of the method are explained in Nan Lin, Yun Zhu, Ruzhong Fan and Momiaoxiong (2017) <DOI:10.1371/journal.pcbi.1005788>.

10-Year Cardiovascular Disease Risk Calculator (QRISK3 2017)
Yan Li <bluefatterplaydota@gmail.com> [aut, cre, trl],
Matthew Sperrin [aut, ctb],
ClinRisk Ltd. [cph],
Tjeerd Pieter van Staa [aut, ths]
This function aims to calculate risk of developing cardiovascular disease of individual patients in next 10 years. The package was based on published risk prediction algorithm <https://qrisk.org/three/src.php>.

c(
person(given = "Peter",
family = "Kochunov",
role = c("aut"),
email = "pkochunov@gmail.com"),
person(given = "Si",
family = "Gao",
role = c("aut", "cre"),
email = "sgao@som.umaryland.edu"),
person(given = "Meghann",
family = "Ryan",
role = c("aut"),
email = "mcryan@som.umaryland.edu")
)
QRI function performs quantile regression analysis using age and sex as predictors to calculate the Quantile Regression Index (QRI) score for each individual’s regional brain imaging metrics and then averages across the regional scores to generate an average tissue specific score for each subject.
Peter Kochunov [aut],
Si Gao [aut, cre],
Meghann Ryan [aut]