iss_source: Find the source of IS by evaluating sharing.

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

Find the source of IS by evaluating sharing.

Description

The function computes the sharing between a reference group of interest for each time point and a selection of groups of interest. In this way it is possible to observe the percentage of shared integration sites between reference and each group and identify in which time point a certain IS was observed for the first time.

Usage

iss_source(
  reference,
  selection,
  ref_group_key = c("SubjectID", "CellMarker", "Tissue", "TimePoint"),
  selection_group_key = c("SubjectID", "CellMarker", "Tissue", "TimePoint"),
  timepoint_column = "TimePoint",
  by_subject = TRUE,
  subject_column = "SubjectID"
)

Arguments

reference	A data frame containing one or more groups of reference. Groups are identified by ref_group_key
selection	A data frame containing one or more groups of interest to compare. Groups are identified by selection_group_key
ref_group_key	Character vector of column names that identify a unique group in the reference data frame
selection_group_key	Character vector of column names that identify a unique group in the selection data frame
timepoint_column	Name of the column holding time point info?
by_subject	Should calculations be performed for each subject separately?
subject_column	Name of the column holding subjects information. Relevant only if by_subject = TRUE

Value

A list of data frames or a data frame

See Also

Other Analysis functions: CIS_grubbs(), HSC_population_size_estimate(), compute_abundance(), cumulative_is(), gene_frequency_fisher(), is_sharing(), 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")
)
df1 <- aggreg |>
    dplyr::filter(.data$Tissue == "BM")
df2 <- aggreg |>
    dplyr::filter(.data$Tissue == "PB")
source <- iss_source(df1, df2)
source
ggplot2::ggplot(source$PT001, ggplot2::aes(
    x = as.factor(g2_TimePoint),
    y = sharing_perc, fill = g1
)) +
    ggplot2::geom_col() +
    ggplot2::labs(
        x = "Time point", y = "Shared IS % with MNC BM",
        title = "Source of is MNC BM vs MNC PB"
    )

calabrialab/ISAnalytics documentation built on Dec. 10, 2024, 10:50 p.m.