| sample_statistics {ISAnalytics} | R Documentation |
Computes user specified functions on numerical columns and updates the metadata data frame accordingly.
Description
![[Experimental]](../help/figures/lifecycle-experimental.svg)
The function operates on a data frame by grouping the content by
the sample key and computing every function specified on every
column in the value_columns parameter. After that the metadata
data frame is updated by including the computed results as columns
for the corresponding key.
For this reason it's required that both x and metadata have the
same sample key, and it's particularly important if the user is
working with previously aggregated data.
For example:
data("integration_matrices", package = "ISAnalytics")
data("association_file", package = "ISAnalytics")
aggreg <- aggregate_values_by_key(
x = integration_matrices,
association_file = association_file,
value_cols = c("seqCount", "fragmentEstimate")
)
aggreg_meta <- aggregate_metadata(association_file = association_file)
sample_stats <- sample_statistics(x = aggreg,
metadata = aggreg_meta,
value_columns = c("seqCount", "fragmentEstimate"),
sample_key = c("SubjectID", "CellMarker","Tissue", "TimePoint"))
Usage
sample_statistics( x, metadata, sample_key = "CompleteAmplificationID", value_columns = "Value", functions = default_stats(), add_integrations_count = TRUE )
Arguments
x |
A data frame |
metadata |
The metadata data frame |
sample_key |
Character vector representing the key for identifying a sample |
value_columns |
The name of the columns to be computed, must be numeric or integer |
functions |
A named list of function or purrr-style lambdas |
add_integrations_count |
Add the count of distinct integration sites
for each group? Can be computed only if |
Value
A list with modified x and metadata data frames
See Also
Other Analysis functions:
CIS_grubbs(),
comparison_matrix(),
compute_abundance(),
cumulative_count_union(),
cumulative_is(),
is_sharing(),
iss_source(),
purity_filter(),
separate_quant_matrices(),
threshold_filter(),
top_integrations()
Examples
data("integration_matrices", package = "ISAnalytics")
data("association_file", package = "ISAnalytics")
stats <- sample_statistics(
x = integration_matrices,
metadata = association_file,
value_columns = c("seqCount", "fragmentEstimate")
)
stats