R codes for the (adaptive) Sum of Powered Score ('SPU' and 'aSPU')
    tests, inverse variance weighted Sum of Powered score ('SPUw' and 'aSPUw') tests
    and gene-based and some pathway based association tests (Pathway based Sum of
    Powered Score tests ('SPUpath'), adaptive 'SPUpath' ('aSPUpath') test, 'GEEaSPU'
    test for multiple traits - single 'SNP' (single nucleotide polymorphism)
    association in generalized estimation equations, 'MTaSPUs' test for multiple
    traits - single 'SNP' association with Genome Wide Association Studies ('GWAS')
    summary statistics, Gene-based Association Test that uses an extended 'Simes'
    procedure ('GATES'), Hybrid Set-based Test ('HYST') and extended version
    of 'GATES' test for pathway-based association testing ('GATES-Simes'). ).
    The tests can be used with genetic and other data sets with covariates. The
    response variable is binary or quantitative. Summary; (1) Single trait-'SNP' set
    association with individual-level data ('aSPU', 'aSPUw', 'aSPUr'), (2) Single trait-'SNP'
    set association with summary statistics ('aSPUs'), (3) Single trait-pathway
    association with individual-level data ('aSPUpath'), (4) Single trait-pathway
    association with summary statistics ('aSPUsPath'), (5) Multiple traits-single
    'SNP' association with individual-level data ('GEEaSPU'), (6) Multiple traits-
    single 'SNP' association with summary statistics ('MTaSPUs'), (7) Multiple traits-'SNP' set association with summary statistics('MTaSPUsSet'), (8) Multiple traits-pathway association with summary statistics('MTaSPUsSetPath').

Assists in automating the selection of terms to include in mixed models when  
  'asreml' is used to fit the models. Procedures are available for choosing models that 
  conform to the hierarchy or marginality principle, for fitting and choosing between 
  two-dimensional spatial models using correlation, natural cubic smoothing spline and 
  P-spline models. A history of the fitting of a sequence of models is kept in a data frame. 
  Also used to compute functions and contrasts of, to investigate differences between and 
  to plot predictions obtained using any model fitting function. The content  falls into 
  the following natural groupings: (i) Data, (ii) Model modification functions, (iii) Model 
  selection and description functions, (iv) Model diagnostics and simulation functions, 
  (v) Prediction production and presentation functions, (vi) Response transformation 
  functions, (vii) Object manipulation functions, and (viii) Miscellaneous functions 
  (for further details see 'asremlPlus-package' in help). The 'asreml' package provides a 
  computationally efficient algorithm for fitting a wide range of linear mixed models using 
  Residual Maximum Likelihood. It is a commercial package and a license for it can be 
  purchased from 'VSNi' <https://vsni.co.uk/> as 'asreml-R', who will supply a zip file 
  for local installation/updating (see <https://asreml.kb.vsni.co.uk/>). It is not needed 
  for functions that are methods for 'alldiffs'  and 'data.frame' objects. The package 
  'asremPlus' can also be installed from <http://chris.brien.name/rpackages/>.