Version: 0.12
Date: 2025-05-13
Title: Mouse Map Converter
Description: Convert mouse genome positions between the build 39 physical map and the genetic map of Cox et al. (2009) <doi:10.1534/genetics.109.105486>.
Author: Karl W Broman ORCID iD [aut, cre]
Maintainer: Karl W Broman <broman@wisc.edu>
Depends: R (≥ 3.5.0)
Imports: Rcpp (≥ 0.12.12)
Suggests: testthat, devtools, roxygen2, qtl2
License: GPL-3
URL: https://github.com/rqtl/mmconvert
BugReports: https://github.com/rqtl/mmconvert/issues
LinkingTo: Rcpp
LazyData: true
Encoding: UTF-8
ByteCompile: true
RoxygenNote: 7.2.3
NeedsCompilation: yes
Packaged: 2025-05-13 14:15:02 UTC; kbroman
Repository: CRAN
Date/Publication: 2025-05-13 14:40:06 UTC

mmconvert: Mouse Map Converter

Description

Function to convert mouse genome positions between the build 39 physical map and the Cox genetic map doi:10.1534/genetics.109.105486.

Useful links

Array annotation information for the mouse MUGA arrays in mouse genome build 39.

Description

A list of four data frames with annotation information for the four MUGA arrays, GigaMUGA ("gm"), MegaMUGA ("mm"), MiniMUGA ("mini") and the original MUGA ("muga"). Each has columns marker, chromosome, build 39 basepair position, and sex-averaged cM position (in Cox Map v3).

Details

SNP probes for the MUGA arrays were blasted against mouse genome build GRCm39 and locations interpolated using revised Cox maps. See https://github.com/kbroman/MUGAarrays for the array annotations and https://github.com/kbroman/CoxMapV3 for the genetic maps. Note that for the genetic map locations, markers were shifted so that 0 cM corresponds to 3 Mbp, using the chromosome- and sex-specific recombination rate. Moreover, the Cox map positions were smoothed slightly to avoid regions with 0 recombination.

Source

https://github.com/kbroman/MUGAarrays

Examples

data(MUGAmaps)

Mouse genetic map based on Cox et al. doi:10.1534/genetics.109.105486, revised for mouse genome build 39.

Description

A data frame with rows being markers and six columns: marker name, chromosome, sex-averaged cM position, female cM position, male cM position, and build 39 basepair position.

Details

Genetic maps were re-estimated after reordering markers according to their position in mouse genome build 39. See https://github.com/kbroman/CoxMapV3. Markers were shifted so that 0 cM corresponds to 3 Mbp, using the chromosome- and sex-specific recombination rate. The maps are smoothed slightly to avoid intervals with 0 recombination.

Source

https://github.com/kbroman/CoxMapV3

Examples

data(coxmap)

Convert a cross2 object to use mouse build GRCm39

Description

Convert a cross2 object (with genotypes from one of the MUGA arrays) to use mouse build GRCm39 and the revised Cox map positions, revising marker order and omitting markers that are not found.

Usage

cross2_to_grcm39(cross, array = c("guess", "gm", "mm", "mini", "muga"))

Arguments

cross

Object of class "cross2", as produced by qtl2::read_cross2(). Must have markers from just one of the MUGA arrays.

array

Character string indicating which of the MUGA arrays was used ("gm" for GigaMUGA, "mm" for MegaMUGA, "mini" for MiniMUGA, or "muga" for the original MUGA), or "guess" (the default) to pick the array with the most matching marker names.

Value

The input cross object with markers subset to those in build GRCm39 and with pmap and gmap replaced with the GRCm39 physical map and revised Cox genetic map, respectively.

See Also

MUGAmaps

Examples


library(qtl2)
file <- paste0("https://raw.githubusercontent.com/rqtl/",
               "qtl2data/main/DOex/DOex.zip")
DOex <- read_cross2(file)
DOex_rev <- cross2_to_grcm39(DOex)

Mouse chromosome lengths in basepairs for build GRCm39

Description

A vector of mouse chromosome lengths in basepairs for mouse genome build GRCm39.

Source

https://www.ncbi.nlm.nih.gov/datasets/genome/GCF_000001635.27/

Examples

data(grcm39_chrlen)

Convert mouse genome positions

Description

Convert mouse genome positions between the build 39 physical map and the Cox genetic map.

Usage

mmconvert(
  positions,
  input_type = c("bp", "Mbp", "ave_cM", "female_cM", "male_cM")
)

Arguments

positions

A set of positions, in one of three possible formats

  • a vector of character strings with like "chr:position", with names being marker names, e.g., c(rs13482072="14:6738536", rs13482231="14:67215850", gnf14.117.278="14:121955310").

  • a list of marker positions, each list being positions on a given chromosome, e.g., list("14"=c(rs13482072=6738536, rs13482231=67215850, gnf14.117.278=121955310)).

  • a data frame with columns chromosome, position, and marker, e.g. data.frame(chr=c(14,14,14), pos=c(6738536, 67215850, 121955310), marker=c("rs13482072", "rs13482231", "gnf14.117.278")).

input_type

Character string indicating the type of positions provided ("bp", "Mbp", "ave_cM", "female_cM", or "male_cM")

Details

We use linear interpolation using the Cox map positions in the object coxmap. For positions outside the range of the markers on the Cox map, we extrapolate using the overall recombination rate.

Value

A data frame with the interpolated positions, with seven columns: marker, chromosome, sex-averaged cM, female cM, male cM, basepairs, and mega-basepairs. The rows are sorted by genomic position.

See Also

coxmap

Examples

# input as character strings like chr:position
input_char <- c(rs13482072="14:6738536", rs13482231="14:67215850", gnf14.117.278="14:121955310")
mmconvert(input_char)

# input as list, as in the map object for R/qtl1 and R/qtl2
input_list <- list("14"=c(rs13482072=6738536, rs13482231=67215850, gnf14.117.278=121955310))
mmconvert(input_list)

# input as data frame; *must* have chr as first column and position as second
# (marker names can be third column, or can be row names)
input_df <- data.frame(chr=c(14,14,14),
                       pos=c(6738536, 67215850, 121955310),
                       marker=c("rs13482072", "rs13482231", "gnf14.117.278"))
mmconvert(input_df)

# input can also be in Mbp
input_df$pos <- input_df$pos / 1e6
mmconvert(input_df, input_type="Mbp")