correlate,AnyHermesData-method | R Documentation |
AnyHermesData
The correlate()
method can calculate the correlation matrix between the sample vectors of
counts from a specified assay. This produces a HermesDataCor
object, which is an extension
of a matrix
with additional quality flags in the slot flag_data
(containing the tech_failure_flag
and low_depth_flag
columns describing the original
input samples).
An autoplot()
method then afterwards can produce the corresponding heatmap.
## S4 method for signature 'AnyHermesData'
correlate(object, assay_name = "counts", method = "pearson", ...)
## S4 method for signature 'HermesDataCor'
autoplot(
object,
flag_colors = c(`FALSE` = "green", `TRUE` = "red"),
cor_colors = circlize::colorRamp2(c(0, 0.5, 1), c("red", "yellow", "green")),
...
)
object |
( |
assay_name |
( |
method |
( |
... |
other arguments to be passed to |
flag_colors |
(named |
cor_colors |
( |
A HermesDataCor
object.
autoplot(HermesDataCor)
: This autoplot()
method uses the ComplexHeatmap::Heatmap()
function
to plot the correlations between samples saved in a HermesDataCor
object.
object <- hermes_data
# Calculate the sample correlation matrix.
correlate(object)
# We can specify another correlation coefficient to be calculated.
result <- correlate(object, method = "spearman")
# Plot the correlation matrix.
autoplot(result)
# We can customize the heatmap.
autoplot(result, show_column_names = FALSE, show_row_names = FALSE)
# Including changing the axis label text size.
autoplot(
result,
row_names_gp = grid::gpar(fontsize = 8),
column_names_gp = grid::gpar(fontsize = 8)
)
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