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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