sequoia (version 2.0.7)

GenoConvert: Convert genotype data

Description

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

Usage

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

Arguments

InFile

character string with name of genotype file to be converted

InFormat

One of 'single', 'double', 'col', 'ped', 'raw', or 'seq', 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, currently only 'seq' and 'col' are implemented.

InData

dataframe or matrix with genotypes to be converted

Missing

vector with symbols interpreted as missing data.

sep

vector with field separator strings that will be tried on InFile. The OutFile separator uses the write.table default, i.e. one blank space

header

a logical value indicating whether the file contains the names of the variables as its first line. If NA (default), set to TRUE for 'raw', and FALSE otherwise.

IDcol

single number giving the column which contains the 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 which contains the individual 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. If 'OutFile' is specified, the matrix is written to this file and nothing is returned inside R. When converting to 0/1/2 format, 2 is the homozygote for the minor allele, and 0 the homozygote for the major allele.

Input formats

The following formats can be specified by InFormat:

single

1 column per marker, otherwise unspecified

double

2 columns per marker, otherwise unspecified

col

(Colony) genotypes are coded as numeric values, missing as 0, in 2 columns per marker. Column 1 contains IDs.

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).

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.

seq

(sequoia) genotypes are coded as 0, 1, 2, missing as \(-9\), in 1 column per marker. Column 1 contains IDs, there is no header row.

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

Error messages

An occasional error when reading in a file with GenoConvert is 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 the matrix, see example.

See Also

CheckGeno, SnpStats, LHConvert

Examples

# NOT RUN {
# 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")

# save time on file conversion next time:
write.table(GenoM, file="Geno_for_sequoia.txt", quote=FALSE,
  col.names=FALSE)
GenoM <- read.table("Geno_for_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)
# }
# NOT RUN {
# }