poppr (version 2.9.6)

read.genalex: Importing data from genalex formatted \*.csv files.

Description

read.genalex will read in a genalex-formatted file that has been exported in a comma separated format and will parse most types of genalex data. The output is a genclone-class or genind-class object.

Usage

read.genalex(
  genalex,
  ploidy = 2,
  geo = FALSE,
  region = FALSE,
  genclone = TRUE,
  sep = ",",
  recode = FALSE
)

Value

A genclone or genind bject.

Arguments

genalex

a \*.csv file exported from genalex

ploidy

an integer to indicate the ploidy of the dataset

geo

indicates the presence of geographic data in the file. This data will be included in a data frame labeled xy in the other() slot.

region

indicates the presence of regional data in the file.

genclone

when TRUE (default), the output will be a genclone object. When FALSE, the output will be a genind object

sep

A character specifying the column separator of the data. Defaults to ",".

recode

For polyploid data: Do you want to recode your data to have varying ploidy? Default is FALSE, and the data will be returned with even ploidy where missing alleles are coded as "0". When TRUE, the data is run through the function recode_polyploids() before being returned. Note that this will prevent conversion to genpop objects in the future. See details.

Author

Zhian N. Kamvar

Details

The resulting genclone-class or genind-class object will have a single strata defined in the strata slot. This will be called "Pop" and will reflect the population factor defined in the genalex input. If region = TRUE, a second column will be inserted and labeled "Region". If you have more than two strata within your data set, you should run the command adegenet::splitStrata() on your data set to define the unique stratifications.

FOR POLYPLOID (> 2n) DATA SETS

The genind object has an all-or-none approach to missing data. If a sample has missing data at a particular locus, then the entire locus is considered missing. This works for diploids and haploids where allelic dosage is unambiguous. For polyploids this poses a problem as much of the data set would be transformed into missing data. With this function, I have created a workaround.

When importing polyploid data sets, missing data is scored as "0" and kept within the genind object as an extra allele. This will break most analyses relying on allele frequencies*. All of the functions in poppr will work properly with these data sets as multilocus genotype analysis is agnostic of ploidy and we have written both Bruvo's distance and the index of association in such a way as to be able to handle polyploids presented in this manner.

\* To restore functionality of analyses relying on allele frequencies, use the recode_polyploids() function.

See Also

genind2genalex(), clonecorrect(), genclone, genind, recode_polyploids()

Examples

if (FALSE) {
Aeut <- read.genalex(system.file("files/rootrot.csv", package="poppr"))

genalex2 <- read.genalex("genalex2.csv", geo=TRUE)
# A genalex file with geographic coordinate data.

genalex3 <- read.genalex("genalex3.csv", region=TRUE) 
# A genalex file with regional information.

genalex4 <- read.genalex("genalex4.csv", region=TRUE, geo=TRUE) 
# A genalex file with both regional and geographic information.
}