Title: | Database Storage of Genotype Probabilities for QTL Mapping |
---|---|
Description: | Uses the 'fst' package to store genotype probabilities on disk for the 'qtl2' package. These genotype probabilities are a central data object for mapping quantitative trait loci (QTL), but they can be quite large. The facilities in this package enable the genotype probabilities to be stored on disk, leading to reduced memory usage with only a modest increase in computation time. |
Authors: | Karl W Broman [aut, cre] , Brian S Yandell [aut] , Petr Simecek [aut] |
Maintainer: | Karl W Broman <[email protected]> |
License: | GPL-3 |
Version: | 0.30 |
Built: | 2024-11-25 16:25:41 UTC |
Source: | CRAN |
Uses a hidden Markov model to calculate the probabilities of the true underlying genotypes given the observed multipoint marker data, with possible allowance for genotyping errors.
calc_genoprob_fst( cross, fbase, fdir = ".", map = NULL, error_prob = 0.0001, map_function = c("haldane", "kosambi", "c-f", "morgan"), lowmem = FALSE, quiet = TRUE, cores = 1, compress = 0, overwrite = FALSE )
calc_genoprob_fst( cross, fbase, fdir = ".", map = NULL, error_prob = 0.0001, map_function = c("haldane", "kosambi", "c-f", "morgan"), lowmem = FALSE, quiet = TRUE, cores = 1, compress = 0, overwrite = FALSE )
cross |
Object of class |
fbase |
Base of filename for fst database. |
fdir |
Directory for fst database. |
map |
Genetic map of markers. May include pseudomarker
locations (that is, locations that are not within the marker
genotype data). If NULL, the genetic map in |
error_prob |
Assumed genotyping error probability |
map_function |
Character string indicating the map function to use to convert genetic distances to recombination fractions. |
lowmem |
If |
quiet |
If |
cores |
Number of CPU cores to use, for parallel calculations.
(If |
compress |
Amount of compression to use (value in the range 0-100; lower values mean larger file sizes) |
overwrite |
If FALSE (the default), refuse to overwrite any files that already exist. |
This is like calling qtl2::calc_genoprob()
and then
fst_genoprob()
, but in a way that hopefully saves memory by
doing it one chromosome at a time.
A list containing the attributes of genoprob
and the address for the created fst database.
Components are:
dim
- List of all dimensions of 3-D arrays.
dimnames
- List of all dimension names of 3-D arrays.
is_x_chr
- Vector of all is_x_chr attributes.
chr
- Vector of (subset of) chromosome names for this object.
ind
- Vector of (subset of) individual names for this object.
mar
- Vector of (subset of) marker names for this object.
fst
- Path and base of file names for the fst database.
qtl2::calc_genoprob()
, fst_genoprob()
library(qtl2) grav2 <- read_cross2(system.file("extdata", "grav2.zip", package="qtl2")) gmap_w_pmar <- insert_pseudomarkers(grav2$gmap, step=1) fst_dir <- file.path(tempdir(), "grav2_genoprob") dir.create(fst_dir) probs_fst <- calc_genoprob_fst(grav2, "grav2", fst_dir, gmap_w_pmar, error_prob=0.002) # clean up: remove all the files we created unlink(fst_files(probs_fst))
library(qtl2) grav2 <- read_cross2(system.file("extdata", "grav2.zip", package="qtl2")) gmap_w_pmar <- insert_pseudomarkers(grav2$gmap, step=1) fst_dir <- file.path(tempdir(), "grav2_genoprob") dir.create(fst_dir) probs_fst <- calc_genoprob_fst(grav2, "grav2", fst_dir, gmap_w_pmar, error_prob=0.002) # clean up: remove all the files we created unlink(fst_files(probs_fst))
Join multiple genotype probability objects, as produced by
fst_genoprob()
for different individuals.
## S3 method for class 'fst_genoprob' cbind(..., fbase = NULL, fdir = NULL, overwrite = FALSE, quiet = FALSE)
## S3 method for class 'fst_genoprob' cbind(..., fbase = NULL, fdir = NULL, overwrite = FALSE, quiet = FALSE)
... |
Genotype probability objects as produced by
|
fbase |
Base of fileame for fst database. Needed if objects have different fst databases. |
fdir |
Directory for fst database. |
overwrite |
If FALSE (the default), refuse to overwrite existing |
quiet |
If TRUE, don't show any messages. Passed to |
A single genotype probability object.
library(qtl2) grav2 <- read_cross2(system.file("extdata", "grav2.zip", package="qtl2")) map <- insert_pseudomarkers(grav2$gmap, step=1) probsA <- calc_genoprob(grav2[1:5,1:2], map, error_prob=0.002) probsB <- calc_genoprob(grav2[1:5,3:4], map, error_prob=0.002) dir <- tempdir() fprobsA <- fst_genoprob(probsA, "exampleAc", dir, overwrite=TRUE) fprobsB <- fst_genoprob(probsB, "exampleBc", dir, overwrite=TRUE) # use cbind to combine probabilities for same individuals but different chromosomes fprobs <- cbind(fprobsA, fprobsB, fbase = "exampleABc", overwrite=TRUE) # clean up: remove all the files we created unlink(fst_files(fprobsA)) unlink(fst_files(fprobsB)) unlink(fst_files(fprobs))
library(qtl2) grav2 <- read_cross2(system.file("extdata", "grav2.zip", package="qtl2")) map <- insert_pseudomarkers(grav2$gmap, step=1) probsA <- calc_genoprob(grav2[1:5,1:2], map, error_prob=0.002) probsB <- calc_genoprob(grav2[1:5,3:4], map, error_prob=0.002) dir <- tempdir() fprobsA <- fst_genoprob(probsA, "exampleAc", dir, overwrite=TRUE) fprobsB <- fst_genoprob(probsB, "exampleBc", dir, overwrite=TRUE) # use cbind to combine probabilities for same individuals but different chromosomes fprobs <- cbind(fprobsA, fprobsB, fbase = "exampleABc", overwrite=TRUE) # clean up: remove all the files we created unlink(fst_files(fprobsA)) unlink(fst_files(fprobsB)) unlink(fst_files(fprobs))
Extract genotype probabilities from fst database as an ordinary calc_genoprob object.
fst_extract(object) fst2calc_genoprob(object)
fst_extract(object) fst2calc_genoprob(object)
object |
Object of class |
The genotype probabilities are extracted from the fst database. Each chromosome is extracted in turn.
An object of class "calc_genoprob"
(a list of 3-dimensional arrays).
fst2calc_genoprob
: Deprecated version (to be deleted)
library(qtl2) grav2 <- read_cross2(system.file("extdata", "grav2.zip", package="qtl2")) map <- insert_pseudomarkers(grav2$gmap, step=1) probs <- calc_genoprob(grav2, map, error_prob=0.002) dir <- tempdir() fprobs <- fst_genoprob(probs, "grav2", dir, overwrite=TRUE) nprobs <- fst_extract(fprobs) # clean up: remove all the files we created unlink(fst_files(fprobs))
library(qtl2) grav2 <- read_cross2(system.file("extdata", "grav2.zip", package="qtl2")) map <- insert_pseudomarkers(grav2$gmap, step=1) probs <- calc_genoprob(grav2, map, error_prob=0.002) dir <- tempdir() fprobs <- fst_genoprob(probs, "grav2", dir, overwrite=TRUE) nprobs <- fst_extract(fprobs) # clean up: remove all the files we created unlink(fst_files(fprobs))
List all of the files used in an fst_genoprob object.
fst_files(object)
fst_files(object)
object |
An object of class |
Vector of character strings with the full paths for all of the files used for the input object
.
library(qtl2) grav2 <- read_cross2(system.file("extdata", "grav2.zip", package="qtl2")) probs <- calc_genoprob(grav2, error_prob=0.002) dir <- tempdir() fprobs <- fst_genoprob(probs, "grav2", dir, overwrite=TRUE) fst_path(fprobs) fst_files(fprobs) # clean up: remove all the files we created unlink(fst_files(fprobs))
library(qtl2) grav2 <- read_cross2(system.file("extdata", "grav2.zip", package="qtl2")) probs <- calc_genoprob(grav2, error_prob=0.002) dir <- tempdir() fprobs <- fst_genoprob(probs, "grav2", dir, overwrite=TRUE) fst_path(fprobs) fst_files(fprobs) # clean up: remove all the files we created unlink(fst_files(fprobs))
Save an R/qtl2 genotype probabilities object to a set of fst files for fast access with reduced memory usage.
fst_genoprob( genoprob, fbase, fdir = ".", compress = 0, verbose = TRUE, overwrite = FALSE, quiet = !verbose )
fst_genoprob( genoprob, fbase, fdir = ".", compress = 0, verbose = TRUE, overwrite = FALSE, quiet = !verbose )
genoprob |
Object of class |
fbase |
Base of filename for fst database. |
fdir |
Directory for fst database. |
compress |
Amount of compression to use (value in the range 0-100; lower values mean larger file sizes) |
verbose |
Opposite of |
overwrite |
If FALSE (the default), refuse to overwrite any files that already exist. |
quiet |
If FALSE (the default), show messages about fst database creation. |
The genotype probabilities are stored in separate databases for each chromosome
as tables of (indivduals*genotypes) x (positions) in directory fst
.
The dim
, dimnames
and is_x_chr
elements of the object
have information about the entire fst database.
If a fst_genoprob
object is a subset of another such object,
the chr
, ind
, and mar
contain information about what is in the subset.
However, the fst
databases are not altered in a subset, and can be restored by
fst_restore()
. The actual elements of an "fst_genoprob"
object are only accessible to the user after a call to unclass()
; instead
the usual access to elements of the object invoke subset.fst_genoprob()
.
A list containing the attributes of genoprob
and the address for the created fst database.
Components are:
dim
- List of all dimensions of 3-D arrays.
dimnames
- List of all dimension names of 3-D arrays.
is_x_chr
- Vector of all is_x_chr attributes.
chr
- Vector of (subset of) chromosome names for this object.
ind
- Vector of (subset of) individual names for this object.
mar
- Vector of (subset of) marker names for this object.
fst
- Path and base of file names for the fst database.
fst_genoprob()
: Deprecated version (to be deleted)
fst_path()
, fst_extract()
, fst_files()
, replace_path()
, fst_restore()
library(qtl2) grav2 <- read_cross2(system.file("extdata", "grav2.zip", package="qtl2")) map <- insert_pseudomarkers(grav2$gmap, step=1) probs <- calc_genoprob(grav2, map, error_prob=0.002) dir <- tempdir() fprobs <- fst_genoprob(probs, "grav2", dir, overwrite=TRUE) # clean up: remove all the files we created unlink(fst_files(fprobs))
library(qtl2) grav2 <- read_cross2(system.file("extdata", "grav2.zip", package="qtl2")) map <- insert_pseudomarkers(grav2$gmap, step=1) probs <- calc_genoprob(grav2, map, error_prob=0.002) dir <- tempdir() fprobs <- fst_genoprob(probs, "grav2", dir, overwrite=TRUE) # clean up: remove all the files we created unlink(fst_files(fprobs))
Get the path used in an fst_genoprob object.
fst_path(object)
fst_path(object)
object |
An object of class |
Character string with path (and initial file stem) for files used in the input object
.
library(qtl2) grav2 <- read_cross2(system.file("extdata", "grav2.zip", package="qtl2")) probs <- calc_genoprob(grav2, error_prob=0.002) dir <- tempdir() fprobs <- fst_genoprob(probs, "grav2", dir, overwrite=TRUE) fst_path(fprobs) fst_files(fprobs) # clean up: remove all the files we created unlink(fst_files(fprobs))
library(qtl2) grav2 <- read_cross2(system.file("extdata", "grav2.zip", package="qtl2")) probs <- calc_genoprob(grav2, error_prob=0.002) dir <- tempdir() fprobs <- fst_genoprob(probs, "grav2", dir, overwrite=TRUE) fst_path(fprobs) fst_files(fprobs) # clean up: remove all the files we created unlink(fst_files(fprobs))
Any "fst_genoprob"
object has embedded its original data and dimensions.
This resets elements ind
, chr
and mar
to the full set.
fst_restore(object) fst_genoprob_restore(object)
fst_restore(object) fst_genoprob_restore(object)
object |
Object of class |
Object is unclassed and elements ind
, chr
and mar
are changed before
reseting attributes as "fst_genoprob"
object.
See fst_genoprob()
for details on the object.
Input object
with dimensions restored.
fst_genoprob_restore()
: Deprecated version (to be removed).
library(qtl2) grav2 <- read_cross2(system.file("extdata", "grav2.zip", package="qtl2")) map <- insert_pseudomarkers(grav2$gmap, step=1) probs <- calc_genoprob(grav2, map, error_prob=0.002) dir <- tempdir() fprobs <- fst_genoprob(probs, "grav2", dir, overwrite=TRUE) # subset probabilities fprobs2 <- subset(fprobs, chr=1:2) # use object to get the full probabilities back fprobs5 <- fst_restore(fprobs2) # clean up: remove all the files we created unlink(fst_files(fprobs))
library(qtl2) grav2 <- read_cross2(system.file("extdata", "grav2.zip", package="qtl2")) map <- insert_pseudomarkers(grav2$gmap, step=1) probs <- calc_genoprob(grav2, map, error_prob=0.002) dir <- tempdir() fprobs <- fst_genoprob(probs, "grav2", dir, overwrite=TRUE) # subset probabilities fprobs2 <- subset(fprobs, chr=1:2) # use object to get the full probabilities back fprobs5 <- fst_restore(fprobs2) # clean up: remove all the files we created unlink(fst_files(fprobs))
Reduce genotype probabilities (as calculated by
qtl2::calc_genoprob()
) to allele probabilities, writing them to an fst database.
genoprob_to_alleleprob_fst( probs, fbase, fdir = ".", quiet = TRUE, cores = 1, compress = 0, overwrite = FALSE )
genoprob_to_alleleprob_fst( probs, fbase, fdir = ".", quiet = TRUE, cores = 1, compress = 0, overwrite = FALSE )
probs |
Genotype probabilities, as calculated from
|
fbase |
Base of filename for fst database. |
fdir |
Directory for fst database. |
quiet |
IF |
cores |
Number of CPU cores to use, for parallel calculations.
(If |
compress |
Amount of compression to use (value in the range 0-100; lower values mean larger file sizes) |
overwrite |
If FALSE (the default), refuse to overwrite any files that already exist. |
This is like calling qtl2::genoprob_to_alleleprob()
and then
fst_genoprob()
, but in a way that hopefully saves memory by
doing it one chromosome at a time.
Link to fst database for the probs
input with probabilities
collapsed to alleles rather than genotypes.
qtl2::genoprob_to_alleleprob()
, fst_genoprob()
library(qtl2) iron <- read_cross2(system.file("extdata", "iron.zip", package="qtl2")) gmap_w_pmar <- insert_pseudomarkers(iron$gmap, step=1) # genotype probabilities fst_dir <- file.path(tempdir(), "iron_genoprob") dir.create(fst_dir) probs_fst <- calc_genoprob_fst(iron, "iron", fst_dir, gmap_w_pmar, error_prob=0.002) # allele probabilities fst_dir_apr <- file.path(tempdir(), "iron_alleleprob") dir.create(fst_dir_apr) aprobs_fst <- genoprob_to_alleleprob_fst(probs_fst, "iron", fst_dir_apr) # clean up: remove all the files we created unlink(fst_files(probs_fst)) unlink(fst_files(aprobs_fst))
library(qtl2) iron <- read_cross2(system.file("extdata", "iron.zip", package="qtl2")) gmap_w_pmar <- insert_pseudomarkers(iron$gmap, step=1) # genotype probabilities fst_dir <- file.path(tempdir(), "iron_genoprob") dir.create(fst_dir) probs_fst <- calc_genoprob_fst(iron, "iron", fst_dir, gmap_w_pmar, error_prob=0.002) # allele probabilities fst_dir_apr <- file.path(tempdir(), "iron_alleleprob") dir.create(fst_dir_apr) aprobs_fst <- genoprob_to_alleleprob_fst(probs_fst, "iron", fst_dir_apr) # clean up: remove all the files we created unlink(fst_files(probs_fst)) unlink(fst_files(aprobs_fst))
Join multiple genotype probability objects, as produced by
fst_genoprob()
for different individuals.
## S3 method for class 'fst_genoprob' rbind(..., fbase = NULL, fdir = NULL, overwrite = FALSE, quiet = FALSE)
## S3 method for class 'fst_genoprob' rbind(..., fbase = NULL, fdir = NULL, overwrite = FALSE, quiet = FALSE)
... |
Genotype probability objects as produced by
|
fbase |
Base of fileame for fst database. Needed if objects have different fst databases. |
fdir |
Directory for fst database. |
overwrite |
If FALSE (the default), refuse to overwrite existing |
quiet |
If TRUE, don't show any messages. Passed to |
A single genotype probability object.
library(qtl2) grav2 <- read_cross2(system.file("extdata", "grav2.zip", package="qtl2")) map <- insert_pseudomarkers(grav2$gmap, step=1) probsA <- calc_genoprob(grav2[1:5,], map, error_prob=0.002) probsB <- calc_genoprob(grav2[6:12,], map, error_prob=0.002) dir <- tempdir() fprobsA <- fst_genoprob(probsA, "exampleAr", dir, overwrite=TRUE) fprobsB <- fst_genoprob(probsB, "exampleBr", dir, overwrite=TRUE) # use rbind to combine probabilities for same chromosomes but different individuals fprobs <- rbind(fprobsA, fprobsB, fbase = "exampleABr") # clean up: remove all the files we created unlink(fst_files(fprobsA)) unlink(fst_files(fprobsB)) unlink(fst_files(fprobs))
library(qtl2) grav2 <- read_cross2(system.file("extdata", "grav2.zip", package="qtl2")) map <- insert_pseudomarkers(grav2$gmap, step=1) probsA <- calc_genoprob(grav2[1:5,], map, error_prob=0.002) probsB <- calc_genoprob(grav2[6:12,], map, error_prob=0.002) dir <- tempdir() fprobsA <- fst_genoprob(probsA, "exampleAr", dir, overwrite=TRUE) fprobsB <- fst_genoprob(probsB, "exampleBr", dir, overwrite=TRUE) # use rbind to combine probabilities for same chromosomes but different individuals fprobs <- rbind(fprobsA, fprobsB, fbase = "exampleABr") # clean up: remove all the files we created unlink(fst_files(fprobsA)) unlink(fst_files(fprobsB)) unlink(fst_files(fprobs))
Replace the path used in an fst_genoprob object.
replace_path(object, path)
replace_path(object, path)
object |
An object of class |
path |
New path (directory + file stem as a single character string) to be used in the object. |
The input object
with the path replaced.
If any of the expected files don't exist with the new path, warnings are issued.
library(qtl2) grav2 <- read_cross2(system.file("extdata", "grav2.zip", package="qtl2")) probs <- calc_genoprob(grav2, error_prob=0.002) dir <- tempdir() fprobs <- fst_genoprob(probs, "grav2", dir, overwrite=TRUE) # move the probabilities into a different directory new_dir <- file.path(tempdir(), "subdir") if(!dir.exists(new_dir)) dir.create(new_dir) for(file in fst_files(fprobs)) { file.rename(file, file.path(new_dir, basename(file))) } # revise the path in fprobs new_path <- sub(dir, new_dir, fst_path(fprobs), fixed=TRUE) fprobs <- replace_path(fprobs, new_path)
library(qtl2) grav2 <- read_cross2(system.file("extdata", "grav2.zip", package="qtl2")) probs <- calc_genoprob(grav2, error_prob=0.002) dir <- tempdir() fprobs <- fst_genoprob(probs, "grav2", dir, overwrite=TRUE) # move the probabilities into a different directory new_dir <- file.path(tempdir(), "subdir") if(!dir.exists(new_dir)) dir.create(new_dir) for(file in fst_files(fprobs)) { file.rename(file, file.path(new_dir, basename(file))) } # revise the path in fprobs new_path <- sub(dir, new_dir, fst_path(fprobs), fixed=TRUE) fprobs <- replace_path(fprobs, new_path)
Pull out a specified set of individuals and/or chromosomes from
the results of fst_genoprob()
.
subset_fst_genoprob(x, ind = NULL, chr = NULL, mar = NULL, ...) ## S3 method for class 'fst_genoprob' subset(x, ind = NULL, chr = NULL, mar = NULL, ...)
subset_fst_genoprob(x, ind = NULL, chr = NULL, mar = NULL, ...) ## S3 method for class 'fst_genoprob' subset(x, ind = NULL, chr = NULL, mar = NULL, ...)
x |
Genotype probabilities as output from |
ind |
A vector of individuals: numeric indices, logical values, or character string IDs |
chr |
A vector of chromosomes: logical values, or character string IDs. Numbers are interpreted as character string IDs. |
mar |
A vector of marker names as character string IDs. |
... |
Ignored. |
The input genotype probabilities, with the selected individuals and/or chromsomes.
library(qtl2) grav2 <- read_cross2(system.file("extdata", "grav2.zip", package="qtl2")) pr <- calc_genoprob(grav2) dir <- tempdir() fpr <- fst_genoprob(pr, "grav2", dir) # keep just individuals 1:5, chromosome 2 prsub <- fpr[1:5,2] # keep just chromosome 2 prsub2 <- fpr[,2] # clean up: remove all the files we created unlink(fst_files(fpr))
library(qtl2) grav2 <- read_cross2(system.file("extdata", "grav2.zip", package="qtl2")) pr <- calc_genoprob(grav2) dir <- tempdir() fpr <- fst_genoprob(pr, "grav2", dir) # keep just individuals 1:5, chromosome 2 prsub <- fpr[1:5,2] # keep just chromosome 2 prsub2 <- fpr[,2] # clean up: remove all the files we created unlink(fst_files(fpr))
Summarize an fst_genoprob object
## S3 method for class 'fst_genoprob' summary(object, ...)
## S3 method for class 'fst_genoprob' summary(object, ...)
object |
An object of class |
... |
Ignored. |
library(qtl2) grav2 <- read_cross2(system.file("extdata", "grav2.zip", package="qtl2")) pr <- calc_genoprob(grav2) dir <- tempdir() fpr <- fst_genoprob(pr, "grav2", dir) # summary of fst_genoprob object summary(fpr) # clean up: remove all the files we created unlink(fst_files(fpr))
library(qtl2) grav2 <- read_cross2(system.file("extdata", "grav2.zip", package="qtl2")) pr <- calc_genoprob(grav2) dir <- tempdir() fpr <- fst_genoprob(pr, "grav2", dir) # summary of fst_genoprob object summary(fpr) # clean up: remove all the files we created unlink(fst_files(fpr))