iss_source {ISAnalytics} | R Documentation

## 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()`, `comparison_matrix()`, `compute_abundance()`, `cumulative_count_union()`, `cumulative_is()`, `is_sharing()`, `purity_filter()`, `sample_statistics()`, `separate_quant_matrices()`, `threshold_filter()`, `top_integrations()`

### 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"
        )

[Package ISAnalytics version 1.4.3 Index]