integration_alluvial_plot {ISAnalytics} | R Documentation

## Alluvial plots for IS distribution in time.

### Description

Alluvial plots allow the visualization of integration sites distribution in different points in time in the same group. This functionality requires the suggested package ggalluvial.

### Usage

    integration_alluvial_plot(
      x,
      group = c("SubjectID", "CellMarker", "Tissue"),
      plot_x = "TimePoint",
      plot_y = "fragmentEstimate_sum_PercAbundance",
      alluvia = mandatory_IS_vars(),
      alluvia_plot_y_threshold = 1,
      top_abundant_tbl = TRUE,
      ...
    )

### Arguments

`x` | A data frame. See details.
`group` | Character vector containing the column names that identify unique groups.
`plot_x` | Column name to plot on the x axis
`plot_y` | Column name to plot on the y axis
`alluvia` | Character vector of column names that uniquely identify alluvia
`alluvia_plot_y_threshold` | Numeric value. Everything below this threshold on y will be plotted in grey and aggregated. See details.
`top_abundant_tbl` | Logical. Produce the summary top abundant tables via top_abund_tableGrob?
`...` | Additional arguments to pass on to top_abund_tableGrob

### Details

#### Input data frame

The input data frame must contain all the columns specified in the arguments `group`, `plot_x`, `plot_y` and `alluvia`. The standard input for this function is the data frame obtained via the compute_abundance function.

#### Plotting threshold on y

The plotting threshold on the quantification on the y axis has the function to highlight only relevant information on the plot and reduce computation time. The default value is 1, that acts on the default column plotted on the y axis which holds a percentage value. This translates in natural language roughly as "highlight with colors only those integrations (alluvia) that at least in 1 point in time have an abundance value >= 1 %". The remaining integrations will be plotted as transparent in the strata.

### Value

For each group a list with the associated plot and optionally the summary tableGrob

### See Also

Other Plotting functions: `CIS_volcano_plot()`, `HSC_population_plot()`, `circos_genomic_density()`, `sharing_heatmap()`, `sharing_venn()`, `top_abund_tableGrob()`

### 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")
    )
    abund <- compute_abundance(x = aggreg)
    alluvial_plots <- integration_alluvial_plot(abund,
        alluvia_plot_y_threshold = 0.5
    )
    ex_plot <- alluvial_plots[[1]]$plot +
        ggplot2::labs(
            title = "IS distribution over time",
            subtitle = "Patient 1, MNC BM",
            y = "Abundance (%)",
            x = "Time point (days after GT)"
        )
    print(ex_plot)

[Package ISAnalytics version 1.4.3 Index]