Package 'pcadapt'

Convert a bed to a matrix

Description

Convert a bed to a matrix

Usage

bed2matrix(bedfile, n = NULL, p = NULL)

Arguments

bedfile	Path to a bed file.
n	Number of samples. Default reads it from corresponding fam file.
p	Number of SNPs. Default reads it from corresponding bim file.

Value

An integer matrix.

Examples

bedfile <- system.file("extdata", "geno3pops.bed", package = "pcadapt")
mat <- bed2matrix(bedfile)
dim(mat)
table(mat)

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Get the principal component the most associated with a genetic marker

Description

get.pc returns a data frame such that each row contains the index of the genetic marker and the principal component the most correlated with it.

Usage

get.pc(x, list)

Arguments

x	an object of class 'pcadapt'.
list	a list of integers corresponding to the indices of the markers of interest.

---

Principal Component Analysis for outlier detection

Description

pcadapt performs principal component analysis and computes p-values to test for outliers. The test for outliers is based on the correlations between genetic variation and the first K principal components. pcadapt also handles Pool-seq data for which the statistical analysis is performed on the genetic markers frequencies. Returns an object of class pcadapt.

Usage

pcadapt(
  input,
  K = 2,
  method = "mahalanobis",
  min.maf = 0.05,
  ploidy = 2,
  LD.clumping = NULL,
  pca.only = FALSE,
  tol = 1e-04
)

## S3 method for class 'pcadapt_matrix'
pcadapt(
  input,
  K = 2,
  method = c("mahalanobis", "componentwise"),
  min.maf = 0.05,
  ploidy = 2,
  LD.clumping = NULL,
  pca.only = FALSE,
  tol = 1e-04
)

## S3 method for class 'pcadapt_bed'
pcadapt(
  input,
  K = 2,
  method = c("mahalanobis", "componentwise"),
  min.maf = 0.05,
  ploidy = 2,
  LD.clumping = NULL,
  pca.only = FALSE,
  tol = 1e-04
)

## S3 method for class 'pcadapt_pool'
pcadapt(
  input,
  K = (nrow(input) - 1),
  method = "mahalanobis",
  min.maf = 0.05,
  ploidy = NULL,
  LD.clumping = NULL,
  pca.only = FALSE,
  tol
)

Arguments

input	The output of function read.pcadapt.
K	an integer specifying the number of principal components to retain.
method	a character string specifying the method to be used to compute the p-values. Two statistics are currently available, "mahalanobis", and "componentwise".
min.maf	Threshold of minor allele frequencies above which p-values are computed. Default is 0.05.
ploidy	Number of trials, parameter of the binomial distribution. Default is 2, which corresponds to diploidy, such as for the human genome.
LD.clumping	Default is NULL and doesn't use any SNP thinning. If you want to use SNP thinning, provide a named list with parameters $size and $thr which corresponds respectively to the window radius and the squared correlation threshold. A good default value would be list(size = 500, thr = 0.1).
pca.only	a logical value indicating whether PCA results should be returned (before computing any statistic).
tol	Convergence criterion of RSpectra::svds(). Default is 1e-4.

Details

First, a principal component analysis is performed on the scaled and centered genotype data. Depending on the specified method, different test statistics can be used.

mahalanobis (default): the robust Mahalanobis distance is computed for each genetic marker using a robust estimate of both mean and covariance matrix between the K vectors of z-scores.

communality: the communality statistic measures the proportion of variance explained by the first K PCs. Deprecated in version 4.0.0.

componentwise: returns a matrix of z-scores.

To compute p-values, test statistics (stat) are divided by a genomic inflation factor (gif) when method="mahalanobis". When using method="mahalanobis", the scaled statistics (chi2_stat) should follow a chi-squared distribution with K degrees of freedom. When using method="componentwise", the z-scores should follow a chi-squared distribution with 1 degree of freedom. For Pool-seq data, pcadapt provides p-values based on the Mahalanobis distance for each SNP.

Value

The returned value is an object of class pcadapt.

---

pcadapt visualization tool

Description

plot.pcadapt is a method designed for objects of class pcadapt. It provides plotting options for quick visualization of pcadapt objects. Different options are currently available : "screeplot", "scores", "stat.distribution", "manhattan" and "qqplot". "screeplot" shows the decay of the genotype matrix singular values and provides a figure to help with the choice of K. "scores" plots the projection of the individuals onto the first two principal components. "stat.distribution" displays the histogram of the selected test statistics, as well as the estimated distribution for the neutral SNPs. "manhattan" draws the Manhattan plot of the p-values associated with the statistic of interest. "qqplot" draws a Q-Q plot of the p-values associated with the statistic of interest.

Usage

## S3 method for class 'pcadapt'
plot(
  x,
  ...,
  option = "manhattan",
  i = 1,
  j = 2,
  pop,
  col,
  chr.info = NULL,
  snp.info = NULL,
  plt.pkg = "ggplot",
  K = NULL
)

Arguments

x	an object of class "pcadapt" generated with pcadapt.
...	...
option	a character string specifying the figures to be displayed. If NULL (the default), all three plots are printed.
i	an integer indicating onto which principal component the individuals are projected when the "scores" option is chosen. Default value is set to 1.
j	an integer indicating onto which principal component the individuals are projected when the "scores" option is chosen. Default value is set to 2.
pop	a list of integers or strings specifying which subpopulation the individuals belong to.
col	a list of colors to be used in the score plot.
chr.info	a list containing the chromosome information for each marker.
snp.info	a list containing the names of all genetic markers present in the input.
plt.pkg	a character string specifying the package to be used to display the graphical outputs. Use "plotly" for interactive plots, or "ggplot" for static plots.
K	an integer specifying the principal component of interest. K has to be specified only when using the "componentwise" method.

Examples

## see ?pcadapt for examples

---

File Converter

Description

read.pcadapt converts genotype matrices or files to an appropriate format readable by pcadapt. For a file as input, you can choose to return either a matrix or convert it in bed/bim/fam files. For a matrix as input, this returns a matrix.

Usage

read.pcadapt(
  input,
  type = c("pcadapt", "lfmm", "vcf", "bed", "ped", "pool", "example"),
  type.out = c("bed", "matrix"),
  allele.sep = c("/", "|"),
  pop.sizes,
  ploidy,
  local.env,
  blocksize
)

Arguments

input	A genotype matrix or a character string specifying the name of the file to be converted. Matrices should use NAs to encode missing values. To encode missing values in 'pcadapt' and 'lfmm' files, 9s should be used.
type	A character string specifying the type of data to be converted from. Converters from 'vcf' and 'ped' formats are not maintained anymore; if you have any issue with those, please use PLINK >= 1.9 to convert them to the 'bed' format.
type.out	Either a bed file or a standard R matrix. If the input is a matrix, then the output is automatically a matrix (so that you don't need to specify this parameter). If the input is a bed file, then the output is also a bed file.
allele.sep	a vector of characters indicating what delimiters are used in VCF files. By default, only "|" and "/" are recognized. So, this argument is only useful for type = "vcf".
pop.sizes	deprecated argument.
ploidy	deprecated argument.
local.env	deprecated argument.
blocksize	deprecated argument.

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Shiny app

Description

pcadapt comes with a Shiny interface.

Usage

run.pcadapt()

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Write PLINK files

Description

Function to write bed/bim/fam files from a pcadapt or an lfmm file.

Usage

writeBed(file, is.pcadapt)

Arguments

file	A pcadapt or lfmm file.
is.pcadapt	a boolean value.

Value

The input 'bedfile' path.

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