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Version 1.4.1 (Aug-23-2024)

• Some warnings were fixed in the documentation as required by CRAN.
• Fixed bugs in functions ‘fitBLUP’, ‘SGP’, ‘getGenCov’: an error was produced if ‘y’ has 2 dimensions but it is a ‘data.frame’. This was fixed by using ‘as.matrix(y)’
• Fixed bug in ‘multitrait.plot’ function
• Fixed bug in checkpoint in function ‘fitBLUP’: an error was produced whenever Z = NULL & K = NULL & ntraits > 1. This error is not produced if an EVD is provided

Version 1.4 (Jun-19-2024)

• Changes in function names: SSI -> SGP, SSI.CV -> SGP.CV. Results from both functions are of the class “SGP” standing for “sparse genomic prediction”
• Training and testing sets in function ‘SGP’ can now be defined using integer vectors as ‘SGP(…,trn, tst)’. In the former version this was defined as ‘SSI(…, trn_tst)’, where ‘trn_tst’ was be a vector with 0’s (for tst) and 1’s (for trn)
• In cross-validation, training set is defined as ‘SGP.CV(…,trn)’. In the former version this was ‘SSI.CV(…,trn_tst)’
• Method ‘fitted’ is replaced by method ‘predict’
• A multi-trait analysis can be performed using the function ‘SGP’ with argument ‘y’ being either a matrix or a vector. In the later case, different genotypes and traits are specified by arguments ‘ID_geno’ and ‘ID_trait’, respectively
• Likewise, for the ‘getGenCov’, arguments ‘ID_geno’ and ‘ID_trait’ can be also used if argument ‘y’ is a vector
• Likewise, for the within-trait analysis of the function ‘fitBLUP’, arguments ‘ID_geno’ and ‘ID_trait’ can be also used if argument ‘y’ is a vector
• Eigenvalues (d) and eigenvectors (U) in functions ‘fitBLUP’ and ‘getGenCov’ can be passed as argument ‘EVD’ being a list as per the function ‘eigen’

Version 1.3.1 (Nov-17-2023)

• Old dependencies R-packages were removed
• Calls to functions ‘Kronecker’ and ‘Kronecker_cov’ from the tensorEVD R-package were added
• Functions to work with triangular matrices were removed

Version 1.3.0 (Aug-15-2023)

New features

• Function ‘fitBLUP’ allows the solution of the mixed model for multiple traits when input ‘y’ has more than one column
• Function ‘getGenCov’ allows the calculation of all pairs of columns of input ‘y’ so a genetic covariance matrix can be formed
• Function ‘SSI’ is extended to the multi-trait case if input ‘y’ has more than one column. In this case within-trait genetic/residual covariances varU and varE are calculated using function ‘getGenCov’ when are not provided
• Arguments ‘trn’ and ‘tst’ in function ‘SSI(…,trn,tst)’ can be be now passed as ‘SSI(…,trn_tst)’, where ‘trn_tst’ can be a vector with 0’s (for tst) and 1’s (for trn)
• New function ‘prune’ added (see manual)
• New functions to work with triangular matrices added (see manual)

Version 1.2.0 (Aug-16-2022)

New features

• Functions ‘solveEN’ and ‘LARS’ allow solving several regressions by iterating over columns of argument ‘Gamma’
• Function ‘SSI’ allows either saving or returning the coefficients through ‘save.beta’ and ‘return.beta’ arguments
• Function ‘SSI’ returns also genetic values ‘u’ of testing subjects
• Methods ‘summary’, ‘fitted’, and ‘plot’ can be implemented for a desired response variable ‘y’ different from the specified in object$y, e.g., fitted(object, y)

Version 1.1.0 (Mar-10-2022)

New features

• Some problems were fixed in the documentation structure as required by CRAN.
• Functions ‘lars2’, ‘SSI_CV’, ‘plotNet’, ‘plotPath’ changed their names to ‘LARS’, ‘SSI.CV’, ‘net.plot’, and ‘path.plot’, respectively.
• Some arguments’ functions changed their names to a more informative name (e.g., ‘minLambda’ => ‘lambda.min’)
• More functionalities added to ‘net.plot’ function

Version 1.0.1 (Jan-26-2022)

New features

• Functions ‘SSI’ and ‘SSI_CV’ allow providing either ‘theta’ (residual/genetic variances ratio) or the ‘h2’ (heritability)

Bug fixes

• C-based routine associated to the ‘readBinary’ function now uses the ‘Rf_allocMatrix’ method to handle matrices whose length (number of rows x number of columns) exceed 2^31-1 = 2147483647

Version 1.0.0 (Sep-30-2021)

New features

• Function ‘solveEN’ allows early stop when a user-provided number of non-zero predictors (at a given value of lambda) is reached (argument ‘maxDF’)
• Functions ‘solveEN’ and ‘lars2’ return object ‘beta’ as matrix with predictors in rows (rather than in columns)
• Function ‘cov2cor2’ allows multiplying the resulting correlation matrix times a constant ‘a’ (default is ‘a=1’)
• Provided ‘wheatHTP’ dataset includes now an array of 4-folds partitions (‘CV’ column in object ‘Y’) and calculations of genetic and residual covariances between YLD and each of the wavelengths (‘genCOV_xy’ and ‘resCOV_xy’ objects), and among YLD from each environment (‘genCOV_yy’ object). Residuals covariances among YLD from each environment (‘resCOV_yy’ object) is also included

Bug fixes

• Function ‘fitBLUP’ performs the new checking varU <= 2*var(y) to declare a possible error if FALSE
• Function reshape2::melt is used instead of reshape::melt

Version 0.4.0 (May-12-2021)

New features

• More detailed functions’ documentation
• Function ‘fitBLUP’ performs a quality control for very small or negatives eigenvalues
• Function ‘saveBinary’ does not save columns’ nor rows’ names anymore
• Function ‘SSI’ uses now a C-based routine called ‘add2diag’ created to add a numeric value to the diagonal of a symmetric matrix (single or double precision). This routine is not at the user level
• Function ‘getGenCov’ has the argument ‘warn’ to whether show warnings from ‘BLUP’ analyses

Bug fixes

• All C-based routines: a ‘long long’ variable type, instead of an ‘int’ type, was used for indexing arrays (matrices). This change allows dealing with matrices whose length (number of rows x number of columns) exceed 2^31-1 = 2147483647 (e.g., a matrix of 46341 x 46341)

Version 0.3.0 (Apr-29-2021)

Features

• First released version
• Function ‘solveMixed’ (from GitHub version) was renamed to ‘fitBLUP’

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.