Is there a way to add confidence intervals to a qqplot?
I have a dataset of gene expression values, which I've visualized using PCA:
pca1 = prcomp(data, scale. = TRUE)
I'm now looking for outliers by checking the distribution of the data against the normal distribution through:
qqnorm(pca1$x,pch = 20, col = c(rep("red", 73), rep("blue", 33)))
qqline(pca1$x)
This is my data:
data = [2.48 104 4.25 219 0.682 0.302 1.09 0.586 90.7 344 13.8 1.17 305 2.8 79.7 3.18 109 0.932 562 0.958 1.87 0.59 114 391 13.5 1.41 208 2.37 166 3.42]
I would now like to plot 95% confidence intervals to check which data points lie outside. Any tips on how to do this?
If the data is normally distributed, the points in a Q-Q plot will lie on a straight diagonal line. Conversely, the more the points in the plot deviate significantly from a straight diagonal line, the less likely the set of data follows a normal distribution.
If the data is non-normal, the points form a curve that deviates markedly from a straight line. Possible outliers are points at the ends of the line, distanced from the bulk of the observations.
The library car
provides the function qqPlot(...)
which adds a pointwise confidence envelope to the normal qq-plot by default:
library(car)
qqPlot(pca1$x)
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