Visualize proportionality and differential proportionality.
# S4 method for propr,missing
plot(x, y, prompt = TRUE, plotly = FALSE)smear(rho, prompt = TRUE, plotly = FALSE)
dendrogram(rho, prompt = TRUE, plotly = FALSE)
bucket(rho, group, k, prompt = TRUE, plotly = FALSE)
prism(rho, k, prompt = TRUE, plotly = FALSE)
bokeh(rho, k, prompt = TRUE, plotly = FALSE)
pca(rho, group, prompt = TRUE, plotly = FALSE)
snapshot(rho, prompt = TRUE, plotly = FALSE)
cytescape(object, col1, col2, prompt = TRUE, d3 = FALSE)
propd2propr(object, ivar)
# S4 method for propd,missing
plot(x, y, cutoff = 1000, col1, col2, propr,
prompt = TRUE, d3 = FALSE, plotSkip = FALSE)
geyser(object, cutoff = 1000, k = 5, prompt = TRUE, plotly = FALSE)
bowtie(object, cutoff = 1000, k = 5, prompt = TRUE, plotly = FALSE)
gemini(object, cutoff = 1000, k = 5, prompt = TRUE, plotly = FALSE)
decomposed(object, cutoff = 1000)
parallel(object, cutoff = 1000, include = NA, or = TRUE,
plotly = FALSE)
A propr or propd object.
Missing. Ignore. Leftover from the generic method definition.
A logical scalar. Set to FALSE to disable
the courtesy prompt when working with big data.
A logical scalar. Set to TRUE to produce
a dynamic plot using the plotly package.
A propr or propd object.
A character vector. Group or sub-group memberships,
ordered according to the row names in counts.
An integer. For propr methods, the number
of co-clusters (where all pairs receive a specified color
if and only if both members belong to same the cluster).
For propd methods, the maximum number of PALs to index
when calculating pals in the network.
A propr or propd object.
A character vector. Specifies which nodes
to color red or blue, respectively.
A character vector. Specifies which nodes
to color red or blue, respectively.
A boolean. Use rgl to plot 3D network.
A numeric scalar. Specifies reference feature(s) for additive log-ratio transformation. The argument will also accept feature name(s) instead of the index position(s). Set to "iqlr" to use inter-quartile log-ratio transformation. Ignore to use centered log-ratio transformation.
For updateCutoffs, a numeric vector.
this argument provides the FDR cutoffs to test.
For graph functions, a numeric scalar. This argument
indicates the maximum theta to include in the figure.
For graph functions, a large integer will instead
retrieve the top N pairs as ranked by theta.
A propr or propd object.
A boolean. Toggles whether to build
the network graph without plotting it.
Used by pals.
This argument indicates which features by
name should belong to a pair for that pair to get included
in the results. Subset performed by
Partner %in% subset | Pair %in% subset.
A boolean. If FALSE, include subsets
by Partner %in% subset & Pair %in% subset.
plot:
A wrapper for smear(x, ...).
smear:
Plots log-ratio transformed abundances pairwise.
Index-aware, meaning that it only plots pairs indexed
in @pairs, unless no pairs are indexed.
Returns a ggplot object.
dendrogram:
Plots a clustering of the proportionality matrix.
Index-aware, meaning that it only plots pairs indexed
in @pairs, unless no pairs are indexed.
Heatmap intensity is not scaled.
Returns a dendrogram object.
bucket:
Plots an estimation of the degree to which a feature pair
differentiates the experimental groups versus the
measure of the proportionality between that feature pair.
The discrimination score is defined as the negative
log of the p-values for each feature in the pair,
computed independently using kruskal.test.
"It's pronounced, 'bouquet'." - Hyacinth Bucket
Returns cluster membership if k is provided.
Otherwise, returns a ggplot object.
prism:
Plots the variance of the ratio of the log-ratio transformed
feature pair (VLR) versus the sum of the individual variances
of each log-ratio transformed feature (VLS). The ratio of
the VLR to the VLS equals 1 - rho. As such, we use
here seven rainbow colored lines to indicate where rho
equals [.01, .05, .50, 0, 1.50, 1.95, 1.99], going
from red to violet.
Returns cluster membership if k is provided.
Otherwise, returns a ggplot object.
bokeh:
Plots the feature variances for each log-ratio transformed
feature pair in the propr object. Highly proportional
pairs will aggregate near the y = x diagonal.
Clusters that appear toward the top-right of the
figure contain features with highly variable abundance across
all samples. Clusters that appear toward the
bottom-left of the figure contain features with fixed
abundance across all samples. Uses a log scale.
Returns cluster membership if k is provided.
Otherwise, returns a ggplot object.
pca:
Plots the first two principal components as calculated
using the log-ratio transformed feature vectors. This
provides a statistically valid alternative to
conventional principal components analysis (PCA).
For more information, see <DOI:10.1139/cjm-2015-0821>.
Returns a ggplot object.
snapshot:
Plots the log-ratio transformed feature abundance as
a heatmap, along with the respective dendrograms.
Heatmap intensity is not scaled.
Returns a dendrogram object.
cytescape:
Builds a table of indexed pairs and their proportionality.
In doing so, this function displays a preview of the
interaction network, built using igraph.
We recommend using the result as input to a
network visualization tool like Cytoscape.
Returns a data.frame of indexed pairs.
propd2propr:
Transforms a propd object into a propr object
where the @matrix slot contains \(1 - \theta\).
Allows the user to interrogate theta using any
visualization built for propr objects.
plot:
Plots the interactions between pairs as a network.
When plotting disjointed proportionality, red edges
indicate that LRM1 > LRM2 while blue edges indicate
that LRM1 < LRM2. When plotting emergent proportionality,
red edges indicate that VLR1 < VLR2 while blue edges
indicate that VLR1 > VLR2. Group labels numbered based on
the order of the group argument to propd.
Use col1 and col2 arguments to color nodes.
For more control over the visualization of the network,
consider exporting the table from shale to a
network visualization tool like Cytoscape.
geyser:
Plots indexed pairs based on the within-group
log-ratio variance (VLR) for each group. Pairs near the
origin show a highly proportional relationship in
both groups. Each line away from the y = x line
indicates a doubling of VLR compared to the other group.
All pairs colored based on PAL
(see: pals).
See gemini.
bowtie:
Plots indexed pairs based on the log-ratio means
(LRM), relative to its PAL, for each group. Pairs near
the origin show comparable LRM, relative to its PAL, in
both groups. Each line away from the y = x line
indicates a doubling of LRM compared to the other group.
All pairs colored based on PAL
(see: pals).
See gemini.
gemini:
Plots indexed pairs based on the log-fold difference
in log-ratio variance (VLR) between the two groups
versus the difference in log-ratio means (LRM). In this
figure, the LRM for each group is signed (i.e., positive
or negative) such that the PAL is the denominator
of the log-ratio. This allows for a fluid comparison
between pairs within the same PAL module. Pairs with a
"Bridged" or "Missing" PAL get excluded from this graph.
Remember that an increase in VLR suggests less
proportionality. All pairs colored based on PAL
(see: pals).
decomposed:
Plots the decomposition of log-ratio variance into
(weighted) group variances and between-group variance.
Useful for visualizing how a theta type selects pairs.
parallel:
Plots the sample-wise log-ratio abundance across all
pairs selected by the provided cutoff. Use the
reference argument to subset the plot to only
include pairs that contain this reference.