Genomic Selection (GS) is a latest development in animal and plant breeding where whole genome markers information is used to predict genetic merit of an individuals in a practical breeding programme. GS is one of the promising tool for improving genetic gain in animal and plants in today’s scenario. This package is basically developed for genomic predictions by estimating marker effects. These marker effects further used for calculation of genotypic merit of individual i.e. genome estimated breeding values (GEBVs). Genomic selection may be based on single trait or multi traits information. This package performs genomic selection only for single traits hence named as STGS i.e. single trait genomic selection. STGS is a comprehensive package which gives single step solution for genomic selection based on most commonly used statistical methods.

In base R, object attributes are lost when objects are modified by
    common data operations such as subset, filter, slice, append, extract
    etc. This packages allows objects to be marked as 'sticky' and have
    attributes persisted during these operations or when inserted
    into or extracted from list-like or table-like objects.

Provides data frames that hold certain columns and attributes 
    persistently for data processing in 'dplyr'.

Manipulating input and output files of the 'STICS' crop
    model. Files are either 'JavaSTICS' XML files or text files used by
    the model 'fortran' executable. Most basic functionalities are reading
    or writing parameter names and values in both XML or text input files,
    and getting data from output files.  Advanced functionalities include
    XML files generation from XML templates and/or spreadsheets, or text
    files generation from XML files by using 'xslt' transformation.

Functions for simplified emulation of time series computer model output in model parameter space using Gaussian processes. Stilt can be used more generally for Kriging of spatio-temporal fields. There are functions to predict at new parameter settings, to test the emulator using cross-validation (which includes information on 95% confidence interval empirical coverage), and to produce contour plots over 2D slices in model parameter space.