PopGenReport (version 2.2.2)

read.genetable: Function to convert textfiles into a genind object (the format required for popgenreport)

Description

This function converts genetic data provided in a tabular 'comma separated value' (.csv) file into a genind object, the data format required to run PopGenReport. At the moment it works only for codominant markers (e.g. microsatellites). This function is based on df2genind from the adegenet package.

Usage

read.genetable(filename, pop = NULL, ind = NULL, lat = NULL, long = NULL,  
x = NULL, y = NULL, other.min = NULL, other.max = NULL, oneColPerAll,  
NA.char = NA, sep = NULL, ncode = NULL, ploidy=2)

Arguments

filename

the name of your file in .csv file format

pop

the column number if subpopulations are known, otherwise set to NULL

ind

the column number of an individual identifier, otherwise set to NULL

lat

the column number where the latitudinal coordinate is recorded (can be set to NULL)

long

the column number where the longitudinal coordinate is recorded (can be set to NULL)

x

the column number where the x coordinate is recorded. If not in Mercator it needs to be transformed!!! (can be set to NULL)

y

the column number where the y coordinate is recorded. If not in Mercator it needs to be transformed!!! (can be set to NULL)

other.min

if your data has some additional data (e.g. gender, size etc.) you can include this data in the genind object as well. Values in this section have to be in adjacent columns with no other columns between them. other.min is the column number where this section starts.

other.max

if your data has some additional data (e.g. gender, size etc.) then you can convert this data as well. This section has to be in a consecutive order with no other type of columns in between. other.max is the column number where this section ends.

oneColPerAll

needs to be specified. If your data is coded as a single column per allele

NA.char

can be NA, 0 or mean. See details section.

sep

a character string separating alleles. See details.

ncode

ploidy

Ploidy of the data set. Be aware that most analysis do only run for diploid data and that missing data in polyploid data sets are ambigious, which may give dubious results if not handled appropriately.

Value

an object of the class genind This kind of object is needed to be passed on to the popgen.report function.

Details

The format of the .csv file is very important. Make sure your headings are exactly as provided in the example file or the conversion will likely fail (e.g. use lower cases for all headings). Use your favourite text editor to reformat the file (e.g. Excel) to prepare the data and save it as csv file. You need to provide the number of columns for each of your data sections. These are: ind, pop, lat, long, other.min, other.max, and whether there is a single column per allele (if you use a single column for both alleles then you need to specify the seperator as well), or two columns per allele. Please refer to the example files to make sure your file is in the correct format and then check the conversion by typing:

mydata <- read.genetable(\"mygeneticdat.csv\") mydata

The easiest way to provide spatial coordinates is to use the read.genetable function and use the lat, long arguments for WGS1984 projected data (the most common projection globally). For additional information how to use spatial data with PopGenReport refer to the help of the popgenreport function and to the popgenreport manual.

=== There are 3 treatments for missing values === - NA: kept as NA.

- 0: allelic frequencies are set to 0 on all alleles of the concerned locus. Recommended for a PCA on compositionnal data.

- \"mean\": missing values are replaced by the mean frequency of the corresponding allele, computed on the whole set of individuals. Recommended for a centred PCA.

=== Details for the sep argument === this character is directly used in reguar expressions like gsub, and thus require some characters to be preceeded by double backslashes. For instance, \"/\" works but \"|\" must be coded as \"\\|\".

See Also

import2genind, df2genind, read.fstat, read.structure, read.genetix read.genepop

Examples

#example file with one column per loci, seperated by forwardslash
read.csv(paste(.libPaths()[1],"/PopGenReport/extdata/platypus1c.csv", sep="" ))
platy1c <- read.genetable( paste(.libPaths()[1],"/PopGenReport/extdata/platypus1c.csv"
, sep="" ), ind=1, pop=2, lat=3, long=4, other.min=5, other.max=6, oneColPerAll=FALSE, 
sep="/", )


#example file with two columns per loci
read.csv(paste(.libPaths()[1],"/PopGenReport/extdata/platypus2c.csv", sep="" ))
platy2c <- read.genetable( paste(.libPaths()[1],"/PopGenReport/extdata/platypus2c.csv",
 sep="" ), ind=1, pop=2, lat=3, long=4, other.min=5, other.max=6, oneColPerAll=TRUE)

#to get a pdf output you need to have a running Latex version installed on your system.
#run a report (with a map)
#res<- popgenreport(platy2c, mk.counts=TRUE, mk.map=TRUE, mk.allele.dist=TRUE, mk.pdf=TRUE)