plotly_FDR: Plot False Discovery Rate (FDR) estimates from output by...

In mixtools: Tools for Analyzing Finite Mixture Models

Plot False Discovery Rate (FDR) estimates from output by EM-like strategies using plotly

Description

This is an updated version of plotFDR. For more technical details, please refer to plotFDR.

Usage

plotly_FDR(post1, post2=NULL, lg1="FDR 1", lg2=NULL, 
          compH0=1, alpha=0.1, complete.data =NULL, pctfdr=0.3,
          col = NULL, width = 3 ,
          title = NULL , title.size = 15 , title.x = 0.5 , title.y = 0.95,
          xlab = "Index" , xlab.size = 15 , xtick.size = 15,
          ylab = "Probability" , ylab.size = 15 , ytick.size = 15,
          legend.text = "" , legend.text.size = 15 , legend.size = 15)

Arguments

post1	The matrix of posterior probabilities from objects such as the output from spEMsymlocN01. The rows need to be sorted by increasing pvalues.
post2	A second object like post1 if comparison is desired, also sorted by increasing pvalues.
lg1	Text describing the FDR estimate in post1.
lg2	Text describing the FDR estimate in post2 if provided.
compH0	The component indicator associated to the null hypothesis H0, normally 1 since it is defined in this way in spEMsymlocN01, but in case of label switching in other algorithms it can be set to 2.
alpha	The target FDR level; the index at which the FDR estimate crosses the horizontal line for level alpha gives the maximum number of cases to reject.
complete.data	An array with n lines and 2 columns, with the component indicator in column 1 and the p-values in column 2, sorted by p-values.
pctfdr	The level up to which the FDR is plotted, i.e. the scale of the vertical axis.
col	Color of traces.
width	Width of traces.
title	Text of the main title.
title.size	Size of the main title.
title.x	Horsizontal position of the main title.
title.y	Vertical posotion of the main title.
xlab	Label of X-axis.
xlab.size	Size of the lable of X-axis.
xtick.size	Size of tick lables of X-axis.
ylab	Label of Y-axis.
ylab.size	Size of the lable of Y-axis.
ytick.size	Size of tick lables of Y-axis.
legend.text	Title of legend.
legend.text.size	Size of the legend title.
legend.size	Size of legend.

Value

A plot of one or two FDR estimates, with the true FDR if available

Author(s)

Didier Chauveau

References

• Chauveau, D., Saby, N., Orton, T. G., Lemercier B., Walter, C. and Arrouys, D. Large-scale simultaneous hypothesis testing in monitoring carbon content from French soil database – A semi-parametric mixture approach, Geoderma 219-220 (2014), 117-124.

See Also

spEMsymlocN01, plotFDR

Examples

## Probit transform of p-values
## from a Beta-Uniform mixture model
## comparion of parametric and semiparametric EM fit
## Note: in actual situations n=thousands
set.seed(50)
n=300 # nb of multiple tests
m=2 # 2 mixture components
a=c(1,0.1); b=c(1,1); lambda=c(0.6,0.4) # parameters
z=sample(1:m, n, rep=TRUE, prob = lambda)
p <- rbeta(n, shape1 = a[z], shape2 = b[z]) # p-values
o <- order(p)
cpd <- cbind(z,p)[o,] # sorted complete data, z=1 if H0, 2 if H1
p <- cpd[,2] # sorted p-values
y <- qnorm(p) # probit transform of the pvalues
# gaussian EM fit with component 1 constrained to N(0,1)
s1 <- normalmixEM(y, mu=c(0,-4),
                  mean.constr = c(0,NA), sd.constr = c(1,NA))
s2 <- spEMsymlocN01(y, mu0 = c(0,-3)) # spEM with N(0,1) fit
plotly_FDR(s1$post, s2$post, lg1 = "normalmixEM", lg2 = "spEMsymlocN01",
           complete.data = cpd) # with true FDR computed from z

mixtools documentation built on Dec. 5, 2022, 5:23 p.m.