read_geno: Data Input

In mmollina/MAPPoly: Genetic Linkage Maps in Autopolyploids

Data Input

Description

Reads an external data file. The format of the file is described in the Details section. This function creates an object of class mappoly.data

Usage

read_geno(
  file.in,
  filter.non.conforming = TRUE,
  elim.redundant = TRUE,
  verbose = TRUE
)

## S3 method for class 'mappoly.data'
print(x, detailed = FALSE, ...)

## S3 method for class 'mappoly.data'
plot(x, thresh.line = 1e-05, ...)

Arguments

file.in	a character string with the name of (or full path to) the input file which contains the data to be read
filter.non.conforming	if TRUE (default) converts data points with unexpected genotypes (i.e. no double reduction) to 'NA'. See function segreg_poly for information on expected classes and their respective frequencies.
elim.redundant	logical. If TRUE (default), removes redundant markers during map construction, keeping them annotated to export to the final map.
verbose	if TRUE (default), the current progress is shown; if FALSE, no output is produced
x	an object of class mappoly.data
detailed	if available, print the number of markers per sequence (default = FALSE)
...	currently ignored
thresh.line	position of a threshold line for p values of the segregation test (default = 10e-06)

Details

The first line of the input file contains the string ploidy followed by the ploidy level of the parents. The second and third lines contain the strings n.ind and n.mrk followed by the number of individuals in the dataset and the total number of markers, respectively. Lines number 4 and 5 contain the strings mrk.names and ind.names followed by a sequence of the names of the markers and the name of the individuals, respectively. Lines 6 and 7 contain the strings dosageP and dosageQ followed by a sequence of numbers containing the dosage of all markers in parent P and Q. Line 8, contains the string seq followed by a sequence of integer numbers indicating the chromosome each marker belongs. It can be any 'a priori' information regarding the physical distance between markers. For example, these numbers could refer to chromosomes, scaffolds or even contigs, in which the markers are positioned. If this information is not available for a particular marker, NA should be used. If this information is not available for any of the markers, the string seq should be followed by a single NA. Line number 9 contains the string seqpos followed by the physical position of the markers into the sequence. The physical position can be given in any unity of physical genomic distance (base pairs, for instance). However, the user should be able to make decisions based on these values, such as the occurrence of crossing overs, etc. Line number 10 should contain the string nphen followed by the number of phenotypic traits. Line number 11 is skipped (Usually used as a spacer). The next elements are strings containing the name of the phenotypic trait with no space characters followed by the phenotypic values. The number of lines should be the same number of phenotypic traits. NA represents missing values. The line number 12 + nphen is skipped. Finally, the last element is a table containing the dosage for each marker (rows) for each individual (columns). NA represents missing values.

Value

An object of class mappoly.data which contains a list with the following components:

ploidy	ploidy level
n.ind	number individuals
n.mrk	total number of markers
ind.names	the names of the individuals
mrk.names	the names of the markers
dosage.p1	a vector containing the dosage in parent P for all n.mrk markers
dosage.p2	a vector containing the dosage in parent Q for all n.mrk markers
chrom	a vector indicating which sequence each marker belongs. Zero indicates that the marker was not assigned to any sequence
genome.pos	Physical position of the markers into the sequence
seq.ref	NULL (unused in this type of data)
seq.alt	NULL (unused in this type of data)
all.mrk.depth	NULL (unused in this type of data)
geno.dose	a matrix containing the dosage for each markers (rows) for each individual (columns). Missing data are represented by ploidy_level + 1
n.phen	number of phenotypic traits
phen	a matrix containing the phenotypic data. The rows correspond to the traits and the columns correspond to the individuals
kept	if elim.redundant = TRUE, holds all non-redundant markers
elim.correspondence	if elim.redundant = TRUE, holds all non-redundant markers and its equivalence to the redundant ones

Author(s)

Marcelo Mollinari, [e-mail]

References

Mollinari M., Olukolu B. A., Pereira G. da S., Khan A., Gemenet D., Yencho G. C., Zeng Z-B. (2020), Unraveling the Hexaploid Sweetpotato Inheritance Using Ultra-Dense Multilocus Mapping, _G3: Genes, Genomes, Genetics_. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1534/g3.119.400620")}

Mollinari, M., and Garcia, A. A. F. (2019) Linkage analysis and haplotype phasing in experimental autopolyploid populations with high ploidy level using hidden Markov models, _G3: Genes, Genomes, Genetics_. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1534/g3.119.400378")}

Examples

#### Tetraploid Example
fl1 = "https://raw.githubusercontent.com/mmollina/MAPpoly_vignettes/master/data/SolCAP_dosage"
tempfl <- tempfile()
download.file(fl1, destfile = tempfl)
SolCAP.dose <- read_geno(file.in  = tempfl)
print(SolCAP.dose, detailed = TRUE)
plot(SolCAP.dose)

mmollina/MAPPoly documentation built on March 8, 2024, 2:04 a.m.