readHMC: Import read depth from UNEAK

In polyRAD: Genotype Calling with Uncertainty from Sequencing Data in Polyploids and Diploids

Import read depth from UNEAK

Description

This function reads the “HapMap.hmc.txt” and “HapMap.fas.txt” files output by the UNEAK pipeline and uses the data to generate a “RADdata” object.

Usage

readHMC(file, includeLoci = NULL, shortIndNames = TRUE, 
        possiblePloidies = list(2), taxaPloidy = 2L, contamRate = 0.001,
        fastafile = sub("hmc.txt", "fas.txt", file, fixed = TRUE))

Arguments

file	Name of the file containing read depth (typically “HapMap.hmc.txt”).
includeLoci	An optional character vector of loci to be included in the output.
shortIndNames	Boolean. If TRUE, taxa names will be shortened with respect to those in the file, eliminating all text after and including the first underscore.
possiblePloidies	A list of numeric vectors indicating potential inheritance modes of SNPs in the dataset. See RADdata.
taxaPloidy	A single integer, or an integer vector with one value per taxon, indicating ploidy. See RADdata.
contamRate	A number ranging from zero to one (typically small) indicating the expected rate of sample cross-contamination.
fastafile	Name of the file containing tag sequences (typically “HapMap.fas.txt”).

Value

A RADdata object containing read depth, taxa and locus names, and nucleotides at variable sites.

Note

UNEAK is not able to report read depths greater than 127, which may be problematic for high depth data on polyploid organisms. The UNEAK pipeline is no longer being updated and is currently only available with archived versions of TASSEL.

Author(s)

Lindsay V. Clark

References

Lu, F., Lipka, A. E., Glaubitz, J., Elshire, R., Cherney, J. H., Casler, M. D., Buckler, E. S. and Costich, D. E. (2013) Switchgrass genomic diversity, ploidy, and evolution: novel insights from a network-based SNP discovery protocol. PLoS Genetics 9, e1003215.

https://www.maizegenetics.net/tassel

https://tassel.bitbucket.io/TasselArchived.html

See Also

readTagDigger, VCF2RADdata, readStacks, readTASSELGBSv2, readDArTag

Examples

# for this example we'll create dummy files rather than using real ones
hmc <- tempfile()
write.table(data.frame(rs = c("TP1", "TP2", "TP3"),
                       ind1_merged_X3 = c("15|0", "4|6", "13|0"),
                       ind2_merged_X3 = c("0|0", "0|1", "0|5"),
                       HetCount_allele1 = c(0, 1, 0),
                       HetCount_allele2 = c(0, 1, 0),
                       Count_allele1 = c(15, 4, 13),
                       Count_allele2 = c(0, 7, 5),
                       Frequency = c(0, 0.75, 0.5)), row.names = FALSE,
            quote = FALSE, col.names = TRUE, sep = "\t", file = hmc)
fas <- tempfile()
writeLines(c(">TP1_query_64",
             "TGCAGAAAAAAAACGCTCGATGCCCCCTAATCCGTTTTCCCCATTCCGCTCGCCCCATCGGAGT",
             ">TP1_hit_64",
             "TGCAGAAAAAAAACGCTCGATGCCCCCTAATCCGTTTTCCCCATTCCGCTCGCCCCATTGGAGT",
             ">TP2_query_64",
             "TGCAGAAAAACAACACCCTAGGTAACAACCATATCTTATATTGCCGAATAAAAAACAACACCCC",
             ">TP2_hit_64",
             "TGCAGAAAAACAACACCCTAGGTAACAACCATATCTTATATTGCCGAATAAAAAATAACACCCC",
             ">TP3_query_64",
             "TGCAGAAAACATGGAGAGGGAGATGGCACGGCAGCACCACCGCTGGTCCGCTGCCCGTTTGCGG",
             ">TP3_hit_64",
             "TGCAGAAAACATGGAGATGGAGATGGCACGGCAGCACCACCGCTGGTCCGCTGCCCGTTTGCGG"),
             fas)

# now read the data
mydata <- readHMC(hmc, fastafile = fas)

# inspect the results
mydata
mydata$alleleDepth
mydata$alleleNucleotides
row.names(mydata$locTable)

polyRAD documentation built on Nov. 10, 2022, 5:14 p.m.