Recombinate Nested Lists to Dataframes (recombinator)
Turns nested lists into data.frames in an orderly manner.

Next-Generation Sequencing (NGS) Data Analysis Toolkit (ngstk)
Can be used to facilitate the analysis of NGS data, such as visualization, conversion of data format for WEB service input and other purpose.

Simple Mediation and Moderation Analysis (medmod)
This toolbox allows you to do simple mediation and moderation analysis. It is also available as a module for ‘jamovi’ (see <https://www.jamovi.org> for more information). ‘Medmod’ is based on the ‘lavaan’ package by Yves Rosseel. You can find an in depth tutorial on the ‘lavaan’ model syntax used for this package on <http://…/index.html>.

Creates Images Sized for Social Media (smpic)
Creates images that are the proper size for social media. Beautiful plots, charts and graphs wither and die if they are not shared. Social media is perfect for this but every platform has its own image dimensions. With ‘smpic’ you can easily save your plots with the exact dimensions needed for the different platforms.

Family Sequence Kernel Association Test for Rare and Common Variants (famSKATRC)
FamSKAT-RC is a family-based association kernel test for both rare and common variants. This test is general and several special cases are known as other methods: famSKAT, which only focuses on rare variants in family-based data, SKAT, which focuses on rare variants in population-based data (unrelated individuals), and SKAT-RC, which focuses on both rare and common variants in population-based data. When one applies famSKAT-RC and sets the value of phi to 1, famSKAT-RC becomes famSKAT. When one applies famSKAT-RC and set the value of phi to 1 and the kinship matrix to the identity matrix, famSKAT-RC becomes SKAT. When one applies famSKAT-RC and set the kinship matrix (fullkins) to the identity matrix (and phi is not equal to 1), famSKAT-RC becomes SKAT-RC. We also include a small sample synthetic pedigree to demonstrate the method with. For more details see Saad M and Wijsman EM (2014) <doi:10.1002/gepi.21844>.

Fitting Semi-Parametric Generalized log-Gamma Regression Models (sglg)
Set of tools to fit a linear multiple or semi-parametric regression models. Under this setup, the localization parameter of the response variable distribution is modeled by using linear multiple regression or semi-parametric functions, whose non-parametric components may be approximated by natural cubic spline or P-splines. The supported distribution for the model error is a generalized log-gamma distribution which includes the generalized extreme value distribution as an important special case.

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