is_sharing: Sharing of integration sites between given groups.

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

Sharing of integration sites between given groups.

Description

Computes the amount of integration sites shared between the groups identified in the input data.

Usage

is_sharing(
  ...,
  group_key = c("SubjectID", "CellMarker", "Tissue", "TimePoint"),
  group_keys = NULL,
  n_comp = 2,
  is_count = TRUE,
  relative_is_sharing = TRUE,
  minimal = TRUE,
  include_self_comp = FALSE,
  keep_genomic_coord = FALSE,
  table_for_venn = FALSE
)

Arguments

...	One or more integration matrices
group_key	Character vector of column names which identify a single group. An associated group id will be derived by concatenating the values of these fields, separated by "_"
group_keys	A list of keys for asymmetric grouping. If not NULL the argument group_key is ignored
n_comp	Number of comparisons to compute. This argument is relevant only if provided a single data frame and a single key.
is_count	Logical, if TRUE returns also the count of IS for each group and the count for the union set
relative_is_sharing	Logical, if TRUE also returns the relative sharing.
minimal	Compute only combinations instead of all possible permutations? If TRUE saves time and excludes redundant comparisons.
include_self_comp	Include comparisons with the same group?
keep_genomic_coord	If TRUE keeps the genomic coordinates of the shared integration sites in a dedicated column (as a nested table)
table_for_venn	Add column with truth tables for venn plots?

Details

An integration site is always identified by the combination of fields in mandatory_IS_vars(), thus these columns must be present in the input(s).

The function accepts multiple inputs for different scenarios, please refer to the vignette vignette("workflow_start", package = "ISAnalytics") for a more in-depth explanation.

Output

The function outputs a single data frame containing all requested comparisons and optionally individual group counts, genomic coordinates of the shared integration sites and truth tables for plotting venn diagrams.

Plotting sharing

The sharing data obtained can be easily plotted in a heatmap via the function sharing_heatmap or via the function sharing_venn

Value

A data frame

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(), compute_abundance(), cumulative_is(), gene_frequency_fisher(), iss_source(), sample_statistics(), top_integrations(), top_targeted_genes()

Examples

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")
)
sharing <- is_sharing(aggreg)
sharing

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