A memory-efficient, visualize-enhanced, parallel-accelerated Genome-Wide Association Study (GWAS) tool. It can
    (1) effectively process large data, 
    (2) rapidly evaluate population structure, 
    (3) efficiently estimate variance components several algorithms, 
    (4) implement parallel-accelerated association tests of markers three methods, 
    (5) globally efficient design on GWAS process computing, 
    (6) enhance visualization of related information. 
    'rMVP' contains three models GLM (Alkes Price (2006) <DOI:10.1038/ng1847>), MLM (Jianming Yu (2006) <DOI:10.1038/ng1702>) 
    and FarmCPU (Xiaolei Liu (2016) <doi:10.1371/journal.pgen.1005767>); variance components estimation methods EMMAX 
    (Hyunmin Kang (2008) <DOI:10.1534/genetics.107.080101>;), FaSTLMM (method: Christoph Lippert (2011) <DOI:10.1038/nmeth.1681>, 
    R implementation from 'GAPIT2': You Tang and Xiaolei Liu (2016) <DOI:10.1371/journal.pone.0107684> and 
    'SUPER': Qishan Wang and Feng Tian (2014) <DOI:10.1371/journal.pone.0107684>), and HE regression 
    (Xiang Zhou (2017) <DOI:10.1214/17-AOAS1052>).

An integrated set of tools to allow data users to conduct 
    meteorological normalisation and counterfactual modelling for air quality 
    data. The meteorological normalisation technique uses predictive random 
    forest models to remove variation of pollutant concentrations so trends and 
    interventions can be explored in a robust way. For examples, see 
    Grange et al. (2018) <doi:10.5194/acp-18-6223-2018> and 
    Grange and Carslaw (2019) <doi:10.1016/j.scitotenv.2018.10.344>. The random
    forest models can also be used for counterfactual or business as usual (BAU) 
    modelling by using the models to predict, from the model's perspective, the 
    future. For an example, see Grange et al. (2021) <doi:10.5194/acp-2020-1171>.

Legacy 'DBI' interface to 'MySQL' / 'MariaDB' based on old code
    ported from S-PLUS. A modern 'MySQL' client written in 'C++' is available
    from the 'RMariaDB' package.