plotFDR: plotFDR

In mcalgaro93/benchdamic: Benchmark of differential abundance methods on microbiome data

plotFDR

Description

Draw the nominal false discovery rates for the 0.01, 0.05, and 0.1 levels.

Usage

plotFDR(df_FDR, cols = NULL)

Arguments

df_FDR	a data.frame produced by the createTIEC function, containing the FDR values.
cols	named vector of colors.

Value

A ggplot object.

Examples

# Load some data
data(ps_stool_16S)

# Generate the patterns for 10 mock comparison for an experiment
# (N = 1000 is suggested)
mocks <- createMocks(nsamples = phyloseq::nsamples(ps_stool_16S), N = 10)
head(mocks)

# Add some normalization/scaling factors to the phyloseq object
my_norm <- setNormalizations(fun = c("norm_edgeR", "norm_CSS"),
    method = c("TMM", "CSS"))
ps_stool_16S <- runNormalizations(normalization_list = my_norm,
    object = ps_stool_16S)

# Initialize some limma based methods
my_limma <- set_limma(design = ~ group, coef = 2,
    norm = c("TMM", "CSS"))

# Run methods on mock datasets
results <- runMocks(mocks = mocks, method_list = my_limma,
    object = ps_stool_16S)

# Prepare results for Type I Error Control
TIEC_summary <- createTIEC(results)

# Plot the results
plotFPR(df_FPR = TIEC_summary$df_FPR)
plotFDR(df_FDR = TIEC_summary$df_FDR)
plotQQ(df_QQ = TIEC_summary$df_QQ, zoom = c(0, 0.1))
plotKS(df_KS = TIEC_summary$df_KS)
plotLogP(df_QQ = TIEC_summary$df_QQ)

mcalgaro93/benchdamic documentation built on March 10, 2024, 10:40 p.m.