View source: R/PlotFunctions.R
pairsGBSR | R Documentation |
Draw a scatter plot of a pair of specified statistics
pairsGBSR(
x,
stats1 = "dp",
stats2 = "missing",
target = "marker",
size = 0.5,
alpha = 0.8,
color = c(Marker = "darkblue", Sample = "darkblue"),
fill = c(Marker = "skyblue", Sample = "skyblue"),
smooth = FALSE
)
x |
A GbsrGenotypeData object. |
stats1 |
A string to specify statistics to be drawn. |
stats2 |
A string to specify statistics to be drawn. |
target |
Either or both of "marker" and "sample", e.g.
|
size |
A numeric value to specify the dot size of a scatter plot. |
alpha |
A numeric value [0-1] to specify the transparency of dots in a scatter plot. |
color |
A named vector "Marker" and "Sample" to specify border color of bins in the histograms. |
fill |
A named vector "Marker" and "Sample" to specify fill color
of bins in the histograms. |
smooth |
A logical value to indicate whether draw a smooth line for
data points. See also |
You can draw a scatter plot of per-marker and/or per-sample summary
statistics specified at stats1
and stats2
. The "stats1" and "stats2"
arguments can take the following values:
Proportion of missing genotype calls.
Proportion of heterozygote calls.
Reference allele frequency.
Total read counts.
Reference allele read counts.
Alternative allele read counts.
Reference allele read frequency.
Mean of reference allele read counts.
Standard deviation of reference allele read counts.
Quantile of reference allele read counts.
Mean of alternative allele read counts.
Standard deviation of alternative allele read counts.
Quantile of alternative allele read counts.
Mapping quality.
Phred-scaled p-value (strand bias)
Variant Quality by Depth
Symmetric Odds Ratio (strand bias)
Alt vs. Ref read mapping qualities
Alt vs. Ref read position bias
Alt Vs. Ref base qualities
To draw scatter plots for "missing", "het", "raf", you need to run
countGenotype()
first to obtain statistics. Similary, "dp",
"ad_ref", "ad_alt", "rrf" requires values obtained via countRead()
.
"mq", "fs", "qd", "sor", "mqranksum", "readposranksum",
and "baseqranksum" only work with target = "marker"
, if your data
contains those values supplied via SNP calling tools like
GATK.
A ggplot object.
# Load data in the GDS file and instantiate a [GbsrGenotypeData] object.
gds_fn <- system.file("extdata", "sample.gds", package = "GBScleanR")
gds <- loadGDS(gds_fn)
# Summarize genotype count information to be used in `pairsGBSR()`
gds <- countGenotype(gds)
# Draw scatter plots of missing rate vs heterozygosity.
pairsGBSR(gds, stats1 = "missing", stats2 = "het")
# Close the connection to the GDS file
closeGDS(gds)
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