Changes in version 4.4                         

  - Now derive a better estimate of the total variance, to get better
    estimates of the variance explained by each PC, especially when
    using clumping.

                         Changes in version 4.0                         

  - read.pcadapt() generates bed files instead of pcadapt files.

  - Computation of PCA is now based on R package RSpectra.

  - Missing values are handled by specifying matrix-vector operations in
    RSpectra that accounts for missing values.

  - Includes LD thinning to compute PCs.

  - No more dependency to R package RcppArmadillo.

  - For Pooled-seq data, use Mahalanobis distances based on PCA
    loadings, no more simulations of individual genotypes.

                         Changes in version 3.1                         

  - Switch from C/Lapack to Rcpp/RcppArmadillo.

  - pcadapt() can take genotype matrices as input.

  - Modified code for binomial sampling.

  - pcadapt() argument clean.files is now deprecated.

  - pcadapt() argument output.filename is now deprecated.

  - read.pcadapt() argument local.env is now deprecated.

  - Latest update of R package vcfR taken into account.

                 Changes in version 3.0.4 (2017-01-02)                  

  - Method based on sampling genotypes added to handle
    pooled-sequencing.

                 Changes in version 3.0.3 (2016-11-03)                  

  - Option type = "vcfR" has been added to read.pcadapt() to overcome
    some conversion issues occurring with VCF files.

  - Argument transpose is now deprecated. Read section A for more
    details.

                 Changes in version 3.0.2 (2016-06-21)                  

  - The function get.pc() has been added. For each SNP, it returns the
    most correlated principal component.

                 Changes in version 3.0.1 (2016-06-14)                  

  - Function read4pcadapt() is now deprecated, it is now called
    read.pcadapt().

  - Using the pop option when plotting scores now provides the color
    legend.

                  Changes in version 3.0 (2016-04-15)                   

  - All analyses are now included in the R package. Users should not use
    the C software PCAdapt fast anymore.

  - Big datasets can be handled directly within the R session.

  - read4pcadapt() now converts files to the pcadapt format.

  - The first argument of pcadapt() can be either a small genotype
    matrix or the output of read4pcadapt().

                  Changes in version 2.2 (2016-02-13)                   

  - The Mahalanobis distance is now estimated from the z-scores rather
    than the loadings.

  - Make sure you have downloaded the latest version of the C software
    PCAdapt (last updated on February 11, 2016).

                  Changes in version 2.1 (2015-12-18)                   

  - The scaling of the SNP before computing PCA has been changed.
    Instead of using standard deviation, we now use the square root of
    $p(1-p)$ (haploid data) or of $2p(1-p)$ (diploid data) where $p$ is
    the minimum allele frequency.

  - Bug fix: the genomic inflation factor has been corrected when K=1.

  - Bug fix: a problem due to high proportion of missing data slowing
    the program has been fixed.

  - Argument "minmaf" has been replaced with "min.maf".

                  Changes in version 2.0 (2015-11-04)                   

  - The default test statistic is not the communality statistic anymore
    but the Mahalanobis distance.

  - Test statistic for Pool-seq data.