View source: R/correlation_functions.R
| corrFeature | R Documentation |
This function plots a scatterplot of two features along with sample correlation statistics.
corrFeature(
aggdat,
feat1,
feat2,
log = TRUE,
method = c("spearman", "pearson", "kendall"),
addRegression = TRUE,
col_by = NULL,
facet1 = NULL,
facet2 = NULL,
plotTitle = "",
xlab = NULL,
ylab = NULL,
allowWebGL = TRUE,
pwidth = 550,
pheight = 200
)
aggdat |
aggregated MRExperiment |
feat1 |
Feature 1. |
feat2 |
Feature 2. |
log |
Log2 transform data. Default is TRUE. |
method |
Correlation coefficient. One of "spearman" (default), "pearson", or "kendall". |
addRegression |
boolean parameter indicating whether linear regression line should be drawn; default: TRUE |
col_by |
Phenotype for coloring. |
facet1 |
Phenotype for facet 1. |
facet2 |
Phenotype for facet 2. |
plotTitle |
Plot title. Default is no title. |
xlab |
X-axis label. Default is |
ylab |
Y-axis label. Default is |
allowWebGL |
boolean indicating if WebGL should be used for large data |
pwidth |
overall plot width; default is 550 |
pheight |
overall plot height; default is 200 |
list holding plotly plot and lm fit
data("mouseData", package = "metagenomeSeq")
aggdat <- aggFeatures(mouseData, level = "genus")
corrFeature(aggdat, feat1 = "Bacteroides", feat2 = "Prevotella")
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