Type: Package
Title: Pattern Support for 'qtl2' Package
Version: 1.2.1
Date: 2023-03-11
Description: Routines in 'qtl2' to study allele patterns in quantitative trait loci (QTL) mapping over a chromosome. Useful in crosses with more than two alleles to identify how sets of alleles, genetically different strands at the same locus, have different response levels. Plots show profiles over a chromosome. Can handle multiple traits together. See https://github.com/byandell/qtl2pattern.
Depends: R (≥ 3.1.0)
Imports: dplyr, tidyr, stringr, ggplot2, assertthat, qtl2, qtl2fst, fst, rlang, stats, graphics
Suggests: knitr, rmarkdown, qtl2ggplot
VignetteBuilder: knitr
License: GPL-3
URL: https://github.com/byandell/qtl2pattern
Encoding: UTF-8
RoxygenNote: 7.2.3
NeedsCompilation: no
Packaged: 2023-03-11 22:10:05 UTC; brianyandell
Author: Brian S Yandell [aut, cre]
Maintainer: Brian S Yandell <brian.yandell@wisc.edu>
Repository: CRAN
Date/Publication: 2023-03-11 22:30:02 UTC

Allele plot for SNPs, alleles and allele pairs

Description

Create table of alleles for various model fits.

Plot alleles for haplotype, diplotype and top patterns and genome position.

Usage

allele1(
  probD,
  phe_df = NULL,
  cov_mx = NULL,
  map = NULL,
  K_chr = NULL,
  patterns = NULL,
  alt = NULL,
  blups = FALSE,
  ...
)

ggplot_allele1(
  object,
  scan1_object = NULL,
  map = NULL,
  pos = NULL,
  trim = TRUE,
  legend.position = "none",
  ...
)

## S3 method for class 'allele1'
autoplot(object, ...)

Arguments

probD

object of class calc_genoprob

phe_df

data frame with one phenotype

cov_mx

covariate matrix

map

Genome map (required if scan1_object present).

K_chr

kinship matrix

patterns

data frame of pattern information

alt

Haplotype allele letter(s) for alternative to reference.

blups

Create BLUPs if TRUE

...

Other parameters ignored.

object

Object of class allele1.

scan1_object

Optional object of class scan1 to find peak.

pos

Genome position in Mbp (supercedes scan1_object).

trim

If TRUE, trim extreme alleles.

legend.position

Legend position (default is "none").

Value

Table with allele effects across sources.

object of class ggplot

Create a function to query genotype probabilities

Description

Create a function that will connect to a database of genotype probability information and return a list with 'probs' object and a 'map' object.

Usage

create_probs_query_func(dbfile, method_val = "fst", probdir_val = "genoprob")

Arguments

dbfile

Name of database file

method_val

either "fst" or "calc" for type of genotype probabilities

probdir_val

name of probability directory (default "genoprob")

Details

Note that this function assumes that probdir_val has a file with the physical map with positions in Mbp and other files with genotype probabilities. See read_probs for details on how probabilities are read. See create_variant_query_func for original idea.

Value

Function with six arguments, 'chr', 'start', 'end', 'allele', 'method' and 'probdir'. It returns a list with 'probs' and 'map' objects spanning the region specified by the first three arguments. The 'probs' element should be either a 'calc_genoprob' or 'fst_genoprob' object (see fst_genoprob).

Examples

dirpath <- "https://raw.githubusercontent.com/rqtl/qtl2data/master/DOex"

create_qv <- function(dirpath) {
  # Download SNP info for DOex from web via RDS.
  # snpinfo is referenced internally in the created function.
  
  tmpfile <- tempfile()
  download.file(file.path(dirpath, "c2_snpinfo.rds"), tmpfile, quiet=TRUE)
  snpinfo <- readRDS(tmpfile)
  unlink(tmpfile)
  snpinfo <- dplyr::rename(snpinfo, pos = pos_Mbp)
  
  function(chr, start, end) {
    if(chr != "2") return(NULL)
    if(start < 96.5) start <- 96.5
    if(end > 98.5) end <- 98.5
    if(start >= end) return(NULL)
    dplyr::filter(snpinfo, .data$pos >= start, .data$pos <= end)
  }
}

query_variants <- create_qv(dirpath)


create_qg <- function(dirpath) {
  # Download Gene info for DOex from web via RDS
  # gene_tbl is referenced internally in the created function.
  
  tmpfile <- tempfile()
  download.file(file.path(dirpath, "c2_genes.rds"), tmpfile, quiet=TRUE)
  gene_tbl <- readRDS(tmpfile)
  unlink(tmpfile)
  
  function(chr, start, end) {
    if(chr != "2") return(NULL)
    if(start < 96.5) start <- 96.5
    if(end > 98.5) end <- 98.5
    if(start >= end) return(NULL)
    dplyr::filter(gene_tbl, .data$end >= start, .data$start <= end)
  }
}

query_genes <- create_qg(dirpath)


# Examples for probs require either FST or RDS storage of data.

Get exons for set of genes

Description

Match up exon start,stop,strand with genes. Use query_genes to find features; see create_gene_query_func.

Returns table of gene and its exons.

Uses gene_exon to plot genes, exons, mRNA with SNPs.

Usage

gene_exon(
  top_snps_tbl,
  feature_tbl = query_genes(chr_id, range_Mbp[1], range_Mbp[2])
)

## S3 method for class 'gene_exon'
summary(object, gene_name = NULL, top_snps_tbl = NULL, extra = 0.005, ...)

## S3 method for class 'gene_exon'
subset(x, gene_val, ...)

ggplot_gene_exon(
  object,
  top_snps_tbl = NULL,
  plot_now = TRUE,
  genes = unique(object$gene),
  ...
)

## S3 method for class 'gene_exon'
autoplot(object, ...)

Arguments

top_snps_tbl

table from top_snps

feature_tbl

table of features from query_genes; see create_gene_query_func

object

Object of class gene_exon.

gene_name

name of gene as character string

extra

extra region beyond gene for SNPs (in Mbp)

...

arguments passed along to gene_exon

x

Object of class gene_exon.

gene_val

Name of gene from object x.

plot_now

plot now if TRUE

genes

Names of genes in object

Value

tbl of exon and gene features

tbl of summary

list of ggplots (see gene_exon)

Author(s)

Brian S Yandell, brian.yandell@wisc.edu

Examples

dirpath <- "https://raw.githubusercontent.com/rqtl/qtl2data/master/DOex"

# Read DOex example cross from 'qtl2data'
DOex <- subset(qtl2::read_cross2(file.path(dirpath, "DOex.zip")), chr = "2")


# Download genotype probabilities
tmpfile <- tempfile()
download.file(file.path(dirpath, "DOex_genoprobs_2.rds"), tmpfile, quiet=TRUE)
pr <- readRDS(tmpfile)
unlink(tmpfile)

# Download SNP info for DOex from web and read as RDS.
tmpfile <- tempfile()
download.file(file.path(dirpath, "c2_snpinfo.rds"), tmpfile, quiet=TRUE)
snpinfo <- readRDS(tmpfile)
unlink(tmpfile)
snpinfo <- dplyr::rename(snpinfo, pos = pos_Mbp)

# Convert to SNP probabilities
snpinfo <- qtl2::index_snps(DOex$pmap, snpinfo)
snppr <- qtl2::genoprob_to_snpprob(pr, snpinfo)

# Scan SNPs.
scan_snppr <- qtl2::scan1(snppr, DOex$pheno)

# Collect top SNPs
top_snps_tbl <- top_snps_pattern(scan_snppr, snpinfo)

# Download Gene info for DOex from web via RDS
tmpfile <- tempfile()
download.file(file.path(dirpath, "c2_genes.rds"), tmpfile, quiet=TRUE)
gene_tbl <- readRDS(tmpfile)
unlink(tmpfile)

# Get Gene exon information.
out <- gene_exon(top_snps_tbl, gene_tbl)
summary(out, gene = out$gene[1])

Collapse genoprob according to pattern

Description

Collapse genoprob according to pattern

Usage

genoprob_to_patternprob(probs1, sdp, alleles = FALSE)

Arguments

probs1

object of class calc_genoprob

sdp

SNP distribution pattern

alleles

use allele string if TRUE

Value

object of class calc_genoprob

Author(s)

Brian S Yandell, brian.yandell@wisc.edu

Examples

dirpath <- "https://raw.githubusercontent.com/rqtl/qtl2data/master/DOex"

# Read DOex example cross from 'qtl2data'
DOex <- subset(qtl2::read_cross2(file.path(dirpath, "DOex.zip")), chr = "2")


# Download genotype probabilities
tmpfile <- tempfile()
download.file(file.path(dirpath, "DOex_genoprobs_2.rds"), tmpfile, quiet=TRUE)
pr <- readRDS(tmpfile)
unlink(tmpfile)

# Convert genotype probabilities to pattern probabilities for pattern 1.
pattern_pr <- genoprob_to_patternprob(pr, 7, TRUE)

str(pr)
str(pattern_pr)

Helper function to set gene locations on plot.

Description

Figure out gene locations to make room for gene names. Written original by Dan Gatti 2013-02-13

Usage

get.gene.locations(
  locs,
  xlim,
  text_size = 3,
  str_rect = c("iW", "i"),
  n_rows = 10,
  plot_width = 6,
  ...
)

Arguments

locs

tbl of gene information

xlim

X axis limits

text_size

size of text (default 3)

str_rect

character spacing on left and right of rectangles (default c("iW","i"))

n_rows

desired number of rows (default 10)

plot_width

width of default plot window (in inches)

...

additional parameters (not used)

Value

list object used by ggplot_feature_tbl

Author(s)

Brian S Yandell, brian.yandell@wisc.edu Daniel Gatti, Dan.Gatti@jax.org

References

https://github.com/dmgatti/DOQTL/blob/master/R/gene.plot.R

Match features with SNPs

Description

Find features that overlap with SNPs

Usage

get_feature_snp(snp_tbl, feature_tbl, extend = 0.005)

Arguments

snp_tbl

tbl of SNPs from assoc.map

feature_tbl

tbl of feature information from create_gene_query_func

extend

extend region for SNPs in Mbp (default 0.005)

Value

tbl of features covering SNPs

Author(s)

Brian S Yandell, brian.yandell@wisc.edu

Match genes with SNPs

Description

Internal routine to find features that overlap with SNPs

Usage

get_gene_snp(
  snp_tbl,
  feature_tbl,
  feature_snp = get_feature_snp(snp_tbl, feature_tbl, 0)
)

Arguments

snp_tbl

tbl of SNPs from query_variants; see package create_variant_query_func

feature_tbl

tbl of feature information from query_genes; see package create_gene_query_func

feature_snp

tbl of feature information from get_feature_snp

Value

tbl of genes covering SNPs

Author(s)

Brian S Yandell, brian.yandell@wisc.edu

Plot of merge_feature object

Description

Merge all SNPs in small region with LOD peaks across multiple phenotype.

Usage

ggplot_merge_feature(object, pheno, plot_by = c("pattern", "consequence"), ...)

## S3 method for class 'merge_feature'
autoplot(object, ...)

merge_feature(
  top_snps_tbl,
  snpinfo,
  out_lmm_snps,
  drop = 1.5,
  dropchar = 0,
  exons = gene_exon(top_snps_tbl)
)

## S3 method for class 'merge_feature'
summary(object, sum_type = c("SNP type", "pattern"), ...)

Arguments

object

of class merge_feature

pheno

name of phenotype to be plotted

plot_by

element to plot by (one of c("pattern","consequence"))

...

other arguments not used

top_snps_tbl

tbl from top_snps_pattern or top_snps

snpinfo

SNP information table

out_lmm_snps

tbl from scan1 on SNPs

drop

include LOD scores within drop of max for each phenotype

dropchar

number of characters to drop on phenames

exons

table from gene_exon

sum_type

one of c("SNP type","pattern")

Value

ggplot2 object

tbl with added information on genes and exons

table summary

Author(s)

Brian S Yandell, brian.yandell@wisc.edu

Examples

dirpath <- "https://raw.githubusercontent.com/rqtl/qtl2data/master/DOex"

# Read DOex example cross from 'qtl2data'
DOex <- subset(qtl2::read_cross2(file.path(dirpath, "DOex.zip")), chr = "2")


# Download genotype probabilities
tmpfile <- tempfile()
download.file(file.path(dirpath, "DOex_genoprobs_2.rds"), tmpfile, quiet=TRUE)
pr <- readRDS(tmpfile)
unlink(tmpfile)

# Download SNP info for DOex from web and read as RDS.
tmpfile <- tempfile()
download.file(file.path(dirpath, "c2_snpinfo.rds"), tmpfile, quiet=TRUE)
snpinfo <- readRDS(tmpfile)
unlink(tmpfile)
snpinfo <- dplyr::rename(snpinfo, pos = pos_Mbp)

# Convert to SNP probabilities
snpinfo <- qtl2::index_snps(DOex$pmap, snpinfo)
snppr <- qtl2::genoprob_to_snpprob(pr, snpinfo)

# Scan SNPs.
scan_snppr <- qtl2::scan1(snppr, DOex$pheno)

# Collect top SNPs
top_snps_tbl <- top_snps_pattern(scan_snppr, snpinfo)
summary(top_snps_tbl)

# Download Gene info for DOex from web via RDS
tmpfile <- tempfile()
download.file(file.path(dirpath, "c2_genes.rds"), tmpfile, quiet=TRUE)
gene_tbl <- readRDS(tmpfile)
unlink(tmpfile)

out <- merge_feature(top_snps_tbl, snpinfo, scan_snppr, exons = gene_tbl)
summary(out, "pattern")

Plot scan pattern usign ggplot2

Description

Plot scan pattern usign ggplot2

Genome scan by pattern set

Usage

ggplot_scan1pattern(
  object,
  map,
  plot_type = c("lod", "coef", "coef_and_lod"),
  patterns = object$patterns$founders,
  columns = 1:3,
  min_lod = 3,
  lodcolumn = seq_along(patterns),
  facet = "pheno",
  ...
)

## S3 method for class 'scan1pattern'
autoplot(object, ...)

scan1pattern(
  probs1,
  phe,
  K = NULL,
  covar = NULL,
  map,
  patterns,
  condense_patterns = TRUE,
  blups = FALSE,
  do_scans = TRUE
)

## S3 method for class 'scan1pattern'
summary(object, map, ...)

Arguments

object

object of class scan1pattern

map

genome map

plot_type

type of plot from c("lod","coef")

patterns

data frame of pattern information

columns

columns used for coef plot

min_lod

minimum LOD peak for contrast to be retained

lodcolumn

columns used for scan1 plot (default all patterns)

facet

Plot facets if multiple phenotypes and patterns provided (default = "pheno").

...

additional parameters passed on to other methods

probs1

object of class calc_genoprob

phe

data frame with one phenotype

K

kinship matrix

covar

covariate matrix

condense_patterns

remove snp_action from contrasts if TRUE

blups

Create BLUPs if TRUE

do_scans

Do scans if TRUE.

Value

object of class ggplot

List containing:

Author(s)

Brian S Yandell, brian.yandell@wisc.edu

Examples

dirpath <- "https://raw.githubusercontent.com/rqtl/qtl2data/master/DOex"

# Read DOex example cross from 'qtl2data'
DOex <- subset(qtl2::read_cross2(file.path(dirpath, "DOex.zip")), chr = "2")


# Download genotype probabilities
tmpfile <- tempfile()
download.file(file.path(dirpath, "DOex_genoprobs_2.rds"), tmpfile, quiet=TRUE)
pr <- readRDS(tmpfile)
unlink(tmpfile)

# Download SNP info for DOex from web and read as RDS.
tmpfile <- tempfile()
download.file(file.path(dirpath, "c2_snpinfo.rds"), tmpfile, quiet=TRUE)
snpinfo <- readRDS(tmpfile)
unlink(tmpfile)
snpinfo <- dplyr::rename(snpinfo, pos = pos_Mbp)

# Convert to SNP probabilities
snpinfo <- qtl2::index_snps(DOex$pmap, snpinfo)
snppr <- qtl2::genoprob_to_snpprob(pr, snpinfo)

# Scan SNPs
scan_snppr <- qtl2::scan1(snppr, DOex$pheno)
top_snps_tbl <- top_snps_pattern(scan_snppr, snpinfo)

# Summarize to find top patterns
patterns <- dplyr::arrange(summary(top_snps_tbl), dplyr::desc(max_lod))

# Scan using patterns.
scan_pat <- scan1pattern(pr, DOex$pheno, map = DOex$pmap, patterns = patterns)

# Summary of scan1pattern.
summary(scan_pat, DOex$pmap)

Extract pattern of diplotypes

Description

Extract pattern of diplotypes

Extract pattern of haplotypes

Usage

pattern_diplos(sdp, haplos, diplos, cont = NULL)

pattern_haplos(sdp, haplos)

Arguments

sdp

vector of sdp from top_snps_pattern

haplos

vector of haplotype names

diplos

vector of diplotype names

cont

vector of types of contrasts (NULL or from c("add","dom","b6r","b6d"))

Value

matrix of diplotype patterns

matrix of haplotype patterns

Author(s)

Brian S Yandell, brian.yandell@wisc.edu

Turn genotype probabilities into labels

Description

Turn genotype probabilities into labels

Usage

pattern_label(genos, allele = TRUE)

pattern_sdp(label, sdp = NULL, geno_names = sort(unique(label)))

Arguments

genos

matrix of genotype probabilities at locus

allele

Driver has alleles if TRUE, otherwise allele pairs.

label

character string from pattern_label

sdp

SNP distribution pattern for plot colors

geno_names

unique genotype names (alleles or allele pairs)

Value

character vector of genotype names.

Read fast database with possible rownames

Description

Read fast database with format fst. Use first column of database (must be named 'ind') as rownames if desired. R/qtl2 routines assume data frames have rownames to use to align individuals.

Usage

read_fast(datapath, columns = NULL, rownames = TRUE)

Arguments

datapath

character string path to database

columns

names or indexes for columns to be extracted

rownames

use first column of rownames if TRUE (can supply column number)

Value

extracted data frame with appropriate rows and columns.

See Also

read_fst

Read genotype probability object from file

Description

Read object from file stored according to method.

Usage

read_probs(
  chr = NULL,
  start_val = NULL,
  end_val = NULL,
  datapath,
  allele = TRUE,
  method,
  probdir = "genoprob"
)

Arguments

chr

vector of chromosome identifiers

start_val, end_val

start and end values in Mbp

datapath

name of folder with Derived Data

allele

read haplotype allele probabilities (if TRUE) or diplotype allele-pair probabilities (if FALSE)

method

method of genoprob storage

probdir

genotype probability directory (default "genoprob")

Value

list with probs = large object of class calc_genoprob and map = physical map for selected chr

Author(s)

Brian S Yandell, brian.yandell@wisc.edu

Convert sdp to pattern

Description

Convert strain distribution pattern (sdp) to letter pattern.

Usage

sdp_to_pattern(sdp, haplos, symmetric = TRUE)

sdp_to_logical(sdp, haplos, symmetric = TRUE)

Arguments

sdp

vector of sdp values

haplos

letter codes for haplotypes (required)

symmetric

make patterns symmetric if TRUE

Value

vector of letter patterns

Author(s)

Brian S Yandell, brian.yandell@wisc.edu

Examples

dirpath <- "https://raw.githubusercontent.com/rqtl/qtl2data/master/DOex"


# Download SNP info for DOex from web and read as RDS.
tmpfile <- tempfile()
download.file(file.path(dirpath, "c2_snpinfo.rds"), tmpfile, quiet=TRUE)
snpinfo <- readRDS(tmpfile)
unlink(tmpfile)
snpinfo <- dplyr::rename(snpinfo, pos = pos_Mbp)

# Extract strain distribution pattern.
sdp <- snpinfo$sdp
# Find out how many alleles.
nallele <- ceiling(log2(max(sdp)))
out <- sdp_to_pattern(sdp, LETTERS[seq_len(nallele)])
# Show most frequent patterns. 
head(rev(sort(c(table(out)))))

Convert SNP info to map

Description

Convert SNP info to map

Usage

snpinfo_to_map(snpinfo)

Arguments

snpinfo

Data frame with SNP information with the following columns (the last three are generally derived from with index_snps):

  • chr - Character string or factor with chromosome

  • pos - Position (in same units as in the "map" attribute in genoprobs.

  • sdp - Strain distribution pattern: an integer, between 1 and 2^n - 2 where n is the number of strains, whose binary encoding indicates the founder genotypes

  • snp - Character string with SNP identifier (if missing, the rownames are used).

  • index - Indices that indicate equivalent groups of SNPs.

  • intervals - Indexes that indicate which marker intervals the SNPs reside.

  • on_map - Indicate whether SNP coincides with a marker in the genoprobs

Value

map as list of vectors of marker positions.

Collapse genoprob according to pattern

Description

Collapse genoprob according to pattern

Usage

snpprob_collapse(
  snpprobs,
  action = c("additive", "add+dom", "non-add", "recessive", "dominant", "basic")
)

Arguments

snpprobs

object of class calc_genoprob

action

SNP gene action type

Value

object of class calc_genoprob

Author(s)

Brian S Yandell, brian.yandell@wisc.edu

Examples

dirpath <- "https://raw.githubusercontent.com/rqtl/qtl2data/master/DOex"

# Read DOex example cross from 'qtl2data'
DOex <- subset(qtl2::read_cross2(file.path(dirpath, "DOex.zip")), chr = "2")


# Download genotype probabilities
tmpfile <- tempfile()
download.file(file.path(dirpath, "DOex_genoprobs_2.rds"), tmpfile, quiet=TRUE)
pr <- readRDS(tmpfile)
unlink(tmpfile)

# Download SNP info for DOex from web and read as RDS.
tmpfile <- tempfile()
download.file(file.path(dirpath, "c2_snpinfo.rds"), tmpfile, quiet=TRUE)
snpinfo <- readRDS(tmpfile)
unlink(tmpfile)
snpinfo <- dplyr::rename(snpinfo, pos = pos_Mbp)

# Convert to snp probabilities
snpinfo <- qtl2::index_snps(DOex$pmap, snpinfo)
snppr <- qtl2::genoprob_to_snpprob(pr, snpinfo)


dim(snppr[[1]])
dim(snpprob_collapse(snppr, "additive")[[1]])

Summary of features with SNP information

Description

Summary of features with SNP information

Usage

## S3 method for class 'feature_snp'
summary(object, ...)

Arguments

object

tbl of feature information from get_feature_snp

...

additional parameters ignored

Value

tbl of feature summaries by type

Author(s)

Brian S Yandell, brian.yandell@wisc.edu

Summary of features

Description

Show count min and max of features by type

Plot genes as rectangles followed by names. Stagger genes for easy reading. Written original by Dan Gatti 2013-02-13

Usage

## S3 method for class 'feature_tbl'
summary(object, major = TRUE, ...)

## S3 method for class 'feature_tbl'
subset(x, start_val = 0, stop_val = max(x$stop), ...)

ggplot_feature_tbl(
  object,
  rect_col = "grey70",
  strand_col = c(`-` = "#1b9e77", `+` = "#d95f02"),
  type_col = c(gene = "black", pseudogene = "#1b9e77", other = "#d95f02"),
  text_size = 3,
  xlim = NULL,
  snp_pos = top_snps_tbl$pos,
  snp_lod = top_snps_tbl$lod,
  top_snps_tbl = NULL,
  snp_col = "grey70",
  extend = 0.005,
  ...
)

## S3 method for class 'feature_tbl'
autoplot(object, ...)

Arguments

object

tbl of gene information from query_variants; see create_variant_query_func

major

if TRUE (default), only summarize genes and exons

...

additional arguments (not used)

x

tbl of feature information from get_feature_snp

start_val, stop_val

start and stop positions for subset

rect_col

fill color of rectangle (default "grey70")

strand_col

edge color of rectangle by strand from object (default -="blue", +="red"; none if NULL)

type_col

color of type from object (default "black" for gene, "blue" for pseudogene; none if NULL)

text_size

size of text (default 3)

xlim

horizontal axis limits (default is range of features)

snp_pos

position of SNPs in bp if used (default NULL)

snp_lod

LOD of SNPs (for color plotting)

top_snps_tbl

table from top_snps

snp_col

color of SNP vertical lines (default "grey70")

extend

extend region for SNPs in bp (default 0.005)

Value

tbl of feature summaries by type

tbl of feature summaries by type

data frame of gene information (invisible)

Author(s)

Brian S Yandell, brian.yandell@wisc.edu

Brian S Yandell, brian.yandell@wisc.edu Daniel Gatti, Dan.Gatti@jax.org

References

https://github.com/dmgatti/DOQTL/blob/master/R/gene.plot.R

Summary of genes overlapping SNPs

Description

Summary of genes overlapping SNPs

Usage

## S3 method for class 'gene_snp'
summary(object, ...)

Arguments

object

tbl of feature information from get_feature_snp

...

additional parameters ignored

Value

tbl of feature summaries by type

Author(s)

Brian S Yandell, brian.yandell@wisc.edu

Top SNPs organized by allele pattern

Description

Separate fine mapping scans by allele pattern.

Usage

top_snps_pattern(
  scan1_output,
  snpinfo,
  drop = 1.5,
  show_all_snps = TRUE,
  haplos
)

## S3 method for class 'top_snps_pattern'
summary(object, sum_type = c("range", "best", "peak"), ...)

## S3 method for class 'top_snps_pattern'
subset(x, start_val = 0, end_val = max(x$pos), pheno = NULL, ...)

Arguments

scan1_output

output of linear mixed model for phename (see scan1)

snpinfo

Data frame with SNP information with the following columns (the last three are generally derived from with index_snps):

  • chr - Character string or factor with chromosome

  • pos - Position (in same units as in the "map" attribute in genoprobs.

  • sdp - Strain distribution pattern: an integer, between 1 and 2^n - 2 where n is the number of strains, whose binary encoding indicates the founder genotypes

  • snp_id - Character string with SNP identifier (if missing, the rownames are used).

  • index - Indices that indicate equivalent groups of SNPs.

  • intervals - Indexes that indicate which marker intervals the SNPs reside.

  • on_map - Indicate whether SNP coincides with a marker in the genoprobs

drop

include all SNPs within drop of max LOD (default 1.5)

show_all_snps

show all SNPs if TRUE

haplos

optional argument identify codes for haplotypes

object

object of class top_snps_tbl

sum_type

type of summary (one of "range","best")

...

additional parameters ignored

x

tbl of feature information from get_feature_snp

start_val, end_val

start and end positions for subset

pheno

phenotype name(s) for subset

Value

table of top_snps at maximum lod for pattern

table summary

subset of x

Author(s)

Brian S Yandell, brian.yandell@wisc.edu

Examples

dirpath <- "https://raw.githubusercontent.com/rqtl/qtl2data/master/DOex"

# Read DOex example cross from 'qtl2data'
DOex <- subset(qtl2::read_cross2(file.path(dirpath, "DOex.zip")), chr = "2")


# Download genotype probabilities
tmpfile <- tempfile()
download.file(file.path(dirpath, "DOex_genoprobs_2.rds"), tmpfile, quiet=TRUE)
pr <- readRDS(tmpfile)
unlink(tmpfile)

# Download SNP info for DOex from web and read as RDS.
tmpfile <- tempfile()
download.file(file.path(dirpath, "c2_snpinfo.rds"), tmpfile, quiet=TRUE)
snpinfo <- readRDS(tmpfile)
unlink(tmpfile)
snpinfo <- dplyr::rename(snpinfo, pos = pos_Mbp)

# Convert to SNP probabilities
snpinfo <- qtl2::index_snps(DOex$pmap, snpinfo)
snppr <- qtl2::genoprob_to_snpprob(pr, snpinfo)

# Scan SNPs.
scan_snppr <- qtl2::scan1(snppr, DOex$pheno)

# Collect top SNPs
top_snps_tbl <- top_snps_pattern(scan_snppr, snpinfo)
summary(top_snps_tbl)

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