compute_abundance: Computes the abundance for every integration event in the...

In calabrialab/ISAnalytics: Analyze gene therapy vector insertion sites data identified from genomics next generation sequencing reads for clonal tracking studies

Computes the abundance for every integration event in the input data frame.

Description

Abundance is obtained for every integration event by calculating the ratio between the single value and the total value for the given group.

Usage

compute_abundance(
  x,
  columns = c("fragmentEstimate_sum"),
  percentage = TRUE,
  key = c("SubjectID", "CellMarker", "Tissue", "TimePoint"),
  keep_totals = FALSE
)

Arguments

x	An integration matrix - aka a data frame that includes the mandatory_IS_vars() as columns. The matrix can either be aggregated (via aggregate_values_by_key()) or not.
columns	A character vector of column names to process, must be numeric or integer columns
percentage	Add abundance as percentage?
key	The key to group by when calculating totals
keep_totals	A value between TRUE, FALSE or df. If TRUE, the intermediate totals for each group will be kept in the output data frame as a dedicated column with a trailing "_tot". If FALSE, totals won't be included in the output data frame. If df, the totals are returned to the user as a separate data frame, together with the abundance data frame.

Details

Abundance will be computed upon the user selected columns in the columns parameter. For each column a corresponding relative abundance column (and optionally a percentage abundance column) will be produced.

Value

Either a single data frame with computed abundance values or a list of 2 data frames (abundance_df, quant_totals)

Required tags

The function will explicitly check for the presence of these tags:

• All columns declared in mandatory_IS_vars()

See Also

Other Analysis functions: CIS_grubbs(), HSC_population_size_estimate(), cumulative_is(), gene_frequency_fisher(), is_sharing(), iss_source(), sample_statistics(), top_integrations(), top_targeted_genes()

Examples

data("integration_matrices", package = "ISAnalytics")
abund <- compute_abundance(
    x = integration_matrices,
    columns = "fragmentEstimate",
    key = "CompleteAmplificationID"
)
head(abund)

calabrialab/ISAnalytics documentation built on Nov. 2, 2023, 8:57 p.m.