View source: R/read.genetable.r
read.genetable | R Documentation |
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.
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
)
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 |
an optional integer giving the number of characters used for coding one genotype at one locus. If not provided, this is determined from data. |
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. |
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 \"\|\".
an object of the class genind This kind of object is needed to be passed on to the popgen.report function.
Bernd Gruber (bernd.gruber@canberra.edu.au)
import2genind
, df2genind
,
read.fstat
, read.structure
,
read.genetix
read.genepop
#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)
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