pvals_Plots: Plots of PERFect p-values
In katiasmirn/PERFect: Permutation filtration for microbiome data

Description Usage Arguments Value Author(s) See Also Examples

Graphical representation of p-values obtained by running PERFect_sim() or PERFect_perm() for jth taxon colored by quantile values of individual filtering loss.

1	pvals_Plots(PERFect, X, quantiles = c(0.25, 0.5, 0.8, 0.9), alpha = 0.1)

`PERFect`	Output of `PERFect_sim()` or `PERFect_perm()` function.
`X`	OTU table, where taxa are columns and samples are rows of the table. It should be a in data frame format with columns corresponding to taxa names.
`quantiles`	Quantile values for coloring, these are set to 25%, 50%, 80% and 90% percentiles of the individual filtering loss values.
`alpha`	Alpha level of the test, set to 0.1 by default.

A list is returned containing:

`df`	Dataframe of taxa names, p-values, Flu values and quantiles.
`p_vals`	Plot of p-values.

Ekaterina Smirnova

PERFect_sim, PERFect_perm

data(mock2)
# Proportion data matrix
Prop <- mock2$Prop

# Counts data matrix
Counts <- mock2$Counts
dim(Counts) # 240x46

# Perform simultaenous filtering of the data
res_sim <- PERFect_sim(X=Counts)
dim(res_sim$filtX)      # 240x10, removing 36 taxa
colnames(res_sim$filtX) # signal taxa

#permutation perfect colored by FLu values
pvals_Plots(PERFect = res_sim, X = Counts, quantiles = c(0.25, 0.5, 0.8, 0.9), alpha=0.05)