NEWS.md

In pcadapt: Fast Principal Component Analysis for Outlier Detection

pcadapt 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.

pcadapt 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.

pcadapt 3.0.4

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

pcadapt 3.0.3

• 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.

pcadapt 3.0.2

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

pcadapt 3.0.1

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

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

pcadapt 3.0

• 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().

pcadapt 2.2

• 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).

pcadapt 2.1

• 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".

pcadapt 2.0

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

• Test statistic for Pool-seq data.

pcadapt documentation built on Aug. 29, 2023, 5:07 p.m.