plotLogP: plotLogP

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

plotLogP

Description

Draw the p-values or the average p-values distribution across the mock comparisons in logarithmic scale.

Usage

plotLogP(df_pval = NULL, df_QQ = NULL, cols = NULL)

Arguments

df_pval	a data.frame produced by the createTIEC function, containing the p-values for each taxon, method, and mock comparison. It is used to draw the negative log10 p-values distribution. If df_pval is supplied, let df_QQ = NULL.
df_QQ	a data.frame produced by the createTIEC function, containing the average p-values for each quantile and method. It is used to draw the negative log10 average p-values distribution. If df_QQ is supplied, let df_pval = NULL.
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 Nov. 28, 2024, 2:16 p.m.