Allows management of 'Meetup' groups via the <https:www.meetup.com/meetup_api/>.
    Provided are a set of functions that enable fetching information of joined meetups, attendance,
    and members. This package requires the use of an API key.

A framework package aimed to provide standardized computational environment for specialist work via object classes to represent the data coded by samples, taxa and segments (i.e. subpopulations, repeated measures). It supports easy processing of the data along with cross tabulation and relational data tables for samples and taxa. An object of class `mefa' is a project specific compendium of the data and can be easily used in further analyses. Methods are provided for extraction, aggregation, conversion, plotting, summary and reporting of `mefa' objects. Reports can be generated in plain text or LaTeX format. Vignette contains worked examples.

An S4 update of the 'mefa' package
  using sparse matrices for enhanced efficiency.
  Sparse array-like objects are supported via
  lists of sparse matrices.

Imports indicator data provided by the Ministry of Education (MoE),Spain. 
  The data is stored at <https://www.educacionyfp.gob.es/servicios-al-ciudadano/estadisticas/no-universitaria.html>
  Includes functions for reading, downloading, and selecting data
  for main series. This package is not sponsored or supported by the MoE Spain.  
  Importa datos con indicadores del Ministerio de Educación y Formación Profesional (MEFD) de Españá. 
  Los datos están en <https://www.educacionyfp.gob.es/servicios-al-ciudadano/estadisticas/no-universitaria.html>
  Contiene funciones para leer, descargar, y seleccionar bases de datos de series principales.
  Este paquete no es patrocinado o respaldado por el MEFD.

Uses as input genetic data that have been reformatted and
     stored in a 'SQLite' database; this database is initially created
     by the standalone 'mega2' C++ program (available freely from
     <https://watson.hgen.pitt.edu/register/>). Loads and manipulates
     data frames containing genotype, phenotype, and family
     information from the input 'SQLite' database, and decompresses
     needed subsets of the genotype data, on the fly, in a memory
     efficient manner.  We have also created several more functions
     that illustrate how to use the data frames as well as perform
     useful tasks: these permit one to run the 'pedgene' package to
     carry out gene-based association tests on family data using
     selected marker subsets, to run the 'SKAT' package to carry out
     gene-based association tests using selected marker subsets, to
     run the 'famSKATRC' package to carry out gene-based association
     tests on families (optionally) and with rare or common variants
     using selected marker subsets, to output the 'Mega2R' data as a
     VCF file and related files (for phenotype and family data), and
     to convert the data frames into CoreArray Genomic Data Structure
     (GDS) format.