HotLoadings.plot_loadings: Plot Loadings the short way

In mcalgaro93/HotLoadings: HotLoadings: a fancy way to plot mixOmics loadings and heatmaps

Description

The user need to be at the end of mixOmics pipeline.

Usage

HotLoadings.plot_loadings(
  PSOBJ,
  format = c("short", "last", "long", "none"),
  data.splsda,
  Y_name,
  component,
  n_top = 15,
  offset = 0.005,
  order = TRUE,
  xlim = c(-0.3, 0.3),
  colors = c("orange", "red", "blue", "dark green")
)

Arguments

PSOBJ	A phyloseq object.
format	"last" if only the deepest taxonomic characterization is needed. "long" if all taxonomic levels are needed. "short" if last 2 known taxonomic levels are needed. "none" for the SV/OTU number only.
data.splsda	A sPLS-DA object from mixomics.
Y_name	A character string indicating which is the variable associated with component specified. Must be a dicothomous variable.
component	A character string containing sPLS-DA's component name.
n_top	An integer number indicating how many top associated features to keep. (Default = 15)
offset	A value indicating the amount of justification from axis for possible plots. (Default = 0.005)
order	A boolean value indicating if the loadings should be separately ordered by positives and negatives (Default = TRUE). If FALSE loadings are ordered using their absolute value.
xlim	Vector of size 2 containings plot limits for x axis of the graphic (default is -0.3, 0.3).
colors	Vector of size 4 containings colors for each class of the graphic. As negative and positive values of the loading has a precise meaning, color order is important. If "Condition 1" is positively associated to specified component (positive loading) and "Condition 2" viceversa: Color1 represents the proportion of negative loading features in "Condition 1" samples; Color2 represents the proportion of negative loading features in "Condition 2" samples; Color3 represents the proportion of positive loading features in "Condition 1" samples; Color4 represents the proportion of positive loading features in "Condition 2" samples;

Value

The function plots loadings with several informations: * n_top associated feature with component; * Relative abundances for each feature in every condition (white numbers); * The proportion between relative abundances for each feature in every condition (length of different colors inside each bar);

See Also

HotLoadings.combine_abundances to create combined condition abundances data frame and HotLoadings.plot_loadings for plot in a single step.

mcalgaro93/HotLoadings documentation built on June 13, 2021, 10:01 p.m.