Convert Genotype Data

Convert genotype data in various formats to sequoia's 1-column-per-marker format, PLINK's ped format, or Colony's 2-columns-per-marker format.

Usage

GenoConvert(
  InData = NULL,
  InFile = NULL,
  InFormat = "raw",
  OutFile = NA,
  OutFormat = "seq",
  Missing = c("-9", "NA", "??", "?", "NULL", "-1", c("0")[InFormat %in% c("col",
    "ped")]),
  sep = c(" ", "\t", ",", ";"),
  header = NA,
  IDcol = NA,
  FIDcol = NA,
  FIDsep = "__",
  dropcol = NA,
  quiet = FALSE
)

Arguments

InData: dataframe, matrix or genlight object with genotypes to be converted.
InFile: character string with name of genotype file to be converted.
InFormat: One of 'seq' (sequoia), 'ped' (PLINK .ped file), 'col' (COLONY), 'raw' (PLINK --recodeA), 'vcf' (requires library {vcfR}), 'single' (1 column per SNP), or 'double' (2 columns per SNP); see Details.
OutFile: character string with name of converted file. If NA, return matrix with genotypes in console (default); if NULL, write to 'GenoForSequoia.txt' in current working directory.
OutFormat: as InFormat; only 'seq', 'col', and 'ped' are implemented. For 'ped' also a sham .map file is created, so that the file can be read by PLINK. Only for 'ped' are extensions .ped & .map added to the specified OutFile filename.
Missing: vector with symbols interpreted as missing data. '0' is missing data for InFormats 'col' and 'ped' only.
sep: vector with field separator strings that will be tried on InFile. Ignored if package data.table is present or if InFormat='vcf'. The OutFile separator uses the write.table default, i.e. one blank space.
header: a logical value indicating whether the file contains a header as its first line. If NA (default), set to TRUE for 'raw', and FALSE otherwise.
IDcol: number giving the column with individual IDs; 0 indicates the rownames (for InData only). If NA (default), set to 2 for InFormat 'raw' and 'ped', and otherwise to 1 for InFile and 0 (rownames) for InData, except when InData has a column labeled 'ID'.
FIDcol: column with the family IDs, if any are wished to be used. This is column 1 for InFormat 'raw' and 'seq', but those are by default not used.
FIDsep: string used to paste FID and IID together into a composite-ID (value passed to paste's collapse). This joining can be reversed using PedStripFID.
dropcol: columns to exclude from the output data, on top of IDcol and FIDcol (which become rownames). When NA, defaults to columns 3-6 for InFormat 'raw' and 'seq'. Can also be used to drop some SNPs, see example below on how to do this for the 2-columns-per-SNP input formats.
quiet: suppress messages and warnings.

Value

A genotype matrix in the specified output format; the default sequoia format ('seq') has 1 column per SNP coded in 0/1/2 format (major homozygote /heterozygote /minor homozygote) with -9 for missing values, sample IDs in row names and SNP names in column names. If 'OutFile' is specified, the matrix is written to this file and nothing is returned inside R.

Details

The first two arguments are interchangeable, and can be given unnamed. The first argument is assumed to be a file name if it is of class 'character' and length 1, and to be the genetic data if it is a matrix or dataframe.

If package data.table is detected, fread is used to read in the data from file. Otherwise, a combination of readLines and strsplit is used.

Input formats

The following formats can be specified by InFormat:

seq: (sequoia) genotypes are coded as 0, 1, 2, missing as \(-9\) (in input any negative number or NA are OK), in 1 column per marker. Column 1 contains IDs, there is no header row.
ped: (PLINK) genotypes are coded as A, C, T, G, missing as 0, in 2 columns per marker. The first 6 columns are descriptive (1:FID, 2:IID, 3 to 6 ignored). If an associated .map file exists, SNP names will be read from there.
raw: (PLINK) genotypes are coded as 0, 1, 2, missing as NA, in 1 column per marker. The first 6 columns are descriptive (1:FID, 2:IID, 3 to 6 ignored), and there is a header row. This is produced by PLINK's option --recodeA
col: (Colony) genotypes are coded as numeric values, missing as 0, in 2 columns per marker. Column 1 contains IDs.
vcf: (VCF) genotypes are coded as '0/0','0/1','1/1', variable number of header rows followed by 1 row per SNP, with various columns of metadata followed by 1 column per individual. Requires package vcfR.
single: 1 column per marker, otherwise unspecified
double: 2 columns per marker, otherwise unspecified

For each InFormat, its default values for Missing, header, IDcol, FIDcol, and dropcol can be overruled by specifying the corresponding input parameters.

Error messages

Occasionally when reading in a file GenoConvert may give an error that 'rows have unequal length'. GenoConvert makes use of readLines and strsplit, which is much faster than read.table for large datafiles, but also more sensitive to unusual line endings, unusual end-of-file characters, or invisible characters (spaces or tabs) after the end of some lines. In these cases, try to read the data from file using read.table or read.csv, and then use GenoConvert on this dataframe or matrix, see example.

Author

Jisca Huisman, jisca.huisman@gmail.com

Examples

if (FALSE) {
# Requires PLINK installed & in system PATH:

# tinker with window size, window overlap and VIF to get a set of
# 400 - 800 markers (100-200 enough for just parentage):
system("cmd", input = "plink --file mydata --indep 50 5 2")
system("cmd", input = "plink --file mydata --extract plink.prune.in
  --recodeA --out PlinkOUT")

GenoM <- GenoConvert(InFile = "PlinkOUT.raw", InFormat='raw')
# which is the same as
GenoM <- GenoConvert(PlinkOUT.raw, InFormat='single',
                    IDcol=2, dropcol=c(1,3:6), header=TRUE)
# (but it will complain that InFormat='single' is not consistent with .raw
# file extension)

# save time on file conversion next time:
write.table(GenoM, file="Geno_sequoia.txt", quote=FALSE, col.names=FALSE)
GenoM <- as.matrix(read.table("Geno_sequoia.txt", row.names=1, header=FALSE))

# drop some SNPs, e.g. after a warning of >2 alleles:
dropSNP <- c(5,68,101,128)
GenoM <- GenoConvert(ColonyFile, InFormat = "col",
                     dropcol = 1 + c(2*dropSNP-1, 2*dropSNP) )

# circumvent a 'rows have unequal length' error:
GenoTmp <- as.matrix(read.table("mydata.txt", header=TRUE, row.names=1))
GenoM <- GenoConvert(InData=GenoTmp, InFormat="single", IDcol=0)

# can also write to file, e.g. simulated genotypes:
GenoConvert(Geno_A, InFormat='seq', OutFormat='ped', OutFile = sim_genotypes)
}