plot.test_snps {gwid}

Line plot of test_snps objects

Description

Line plot of test_snps objects

Usage

## S3 method for class 'test_snps'
plot(
  x,
  y = NA,
  title,
  snp_start,
  snp_end,
  ly = TRUE,
  line_size = 0.6,
  log_transformation = TRUE,
  QQplot = FALSE,
  ...
)

Arguments

x

an object of class test_snps.

y

default value is NA, if specified it should be a vector of names of subject groups i.e. y = c("case","control")

title

title of the plot.

snp_start

select starting position of snps.

snp_end

select ending position of snps.

ly

if 'TRUE', we have a 'plotly' object and if it is 'FALSE' plot is going to be a 'ggplot' object.

line_size

geom_line size

log_transformation

if 'TRUE' plot -log10 transformation of p_values.

QQplot

if TRUE, plot QQplot of P-values

...

other variables

Value

an interactive line plot of test_snps objects for each case control subjects.

Examples

piggyback::pb_download(repo = "soroushmdg/gwid",tag = "v0.0.1",dest = tempdir())
ibd_data_file <- paste0(tempdir(),"//chr3.ibd")
genome_data_file <- paste0(tempdir(),"//chr3.gds")
phase_data_file <- paste0(tempdir(),"//chr3.vcf")
case_control_data_file <- paste0(tempdir(),"//case-cont-RA.withmap.Rda")
# case-control data
case_control <- gwid::case_control(case_control_rda = case_control_data_file)
names(case_control) #cases and controls group
summary(case_control) # in here, we only consider cases,cont1,cont2,cont3 groups in the study
case_control$cases[1:3] # first three subject names of cases group
# read SNP data (use SNPRelate to convert it to gds) and count number of minor alleles
snp_data_gds <- gwid::build_gwas(gds_data = genome_data_file,
caco = case_control,gwas_generator = TRUE)
class(snp_data_gds)
names(snp_data_gds)
head(snp_data_gds$snps) # it has information about counts of minor alleles in each location.
# read haplotype data (output of beagle)
haplotype_data <- gwid::build_phase(phased_vcf = phase_data_file,caco = case_control)
class(haplotype_data)
names(haplotype_data)
dim(haplotype_data$Hap.1) #22302 SNP and 1911 subjects
# read IBD data (output of Refined-IBD)
ibd_data <- gwid::build_gwid(ibd_data = ibd_data_file,gwas = snp_data_gds)
class(ibd_data)
ibd_data$ibd # refined IBD output
ibd_data$res # count number of IBD for each SNP location
# plot count of IBD in chromosome 3
plot(ibd_data,y = c("cases","cont1"),ly = FALSE)
# Further investigate location between 117M and 122M
# significant number of IBD's in group cases, compare to cont1, cont2 and cont3.
plot(ibd_data,y = c("cases","cont1"),snp_start = 119026294,snp_end = 120613594,ly = FALSE)
model_fisher <- gwid::fisher_test(ibd_data,case_control,reference = "cases",
snp_start = 119026294,snp_end = 120613594)
class(model_fisher)
plot(model_fisher, y = c("cases","cont1"),ly = FALSE)
hap_str <- gwid::haplotype_structure(ibd_data,phase = haplotype_data,w = 10,
snp_start = 119026294,snp_end = 120613594)
haplo_freq <- gwid::haplotype_frequency(hap_str)
plot(haplo_freq,y = c("cases", "cont1"),plot_type = "haplotype_structure_frequency",
nwin = 1, type = "version1",ly = FALSE)