barcode_ggheatmap_stat {barcodetrackR} | R Documentation

## Barcode Top Clone Heatmap

### Description

Creates a heatmap from the columns of data in the Summarized Experiment object, with the option to label based on statistical analysis. Uses ggplot2.

### Usage

    barcode_ggheatmap_stat(
      your_SE,
      sample_size,
      stat_test = "chi-squared",
      stat_option = "subsequent",
      reference_sample = NULL,
      stat_display = "top",
      show_all_significant = FALSE,
      p_threshold = 0.05,
      p_adjust = "none",
      bc_threshold = 0,
      plot_labels = NULL,
      n_clones = 10,
      cellnote_assay = "stars",
      your_title = NULL,
      grid = TRUE,
      label_size = 12,
      dendro = FALSE,
      cellnote_size = 4,
      distance_method = "Euclidean",
      minkowski_power = 2,
      hclust_linkage = "complete",
      row_order = "hierarchical",
      clusters = 0,
      percent_scale = c(0, 2.5e-05, 0.001, 0.01, 0.1, 1),
      color_scale = c("#4575B4", "#4575B4", "lightblue", "#fefeb9", "#D73027", "red4"),
      return_table = FALSE
    )

### Arguments

`your_SE` | A Summarized Experiment object.
`sample_size` | A numeric vector providing the sample size of each column of the SummarizedExperiment passed to the function. This sample size describes the samples that the barcoding data is meant to approximate.
`stat_test` | The statistical test to use on the constructed contingency table for each barcoe. Options are "chi-squared" and "fisher."
`stat_option` | For "subsequent" statistical testing is performed on each column of data compared to the column before it. For "reference," all other columns of data are compared to a reference column.
`reference_sample` | Provide the column name of the reference column if stat_option is set to "reference." Defaults to the first column in the SummarizedExperiment.
`stat_display` | Choose which clones to display on the heatmap. IF set to "top," the top n_clones ranked by abundance for each sample will be displayed. If set to "change," the top n_clones with the lowest p-value from statistical testing will be shown for each sample. If set to "increase," the top n_clones (ranked by p-value) which increase in abundance for each sample will be shown. And if set to "decrease," the top n_clones (ranked by lowest p-value) which decrease in abdundance will be shown.
`show_all_significant` | Logical. If set to TRUE when stat_display = "change," "increase," or "decrease" then the n_clones argument will be overriden and all clones with a statistically singificant change, increase, or decrease in proportion will be shown.
`p_threshold` | The p_value threshold to use for statistical testing
`p_adjust` | Character, default = "none". To correct p-values for muiltiple comparisons, set to any of the p value adjustment methods in the p.adjust function in R stats, which includes "holm", "hochberg", "hommel", "bonferroni", "BH", "BY", and "fdr".
`bc_threshold` | Clones must be above this proportion in at least one sample to be included in statistical testing.
`plot_labels` | Vector of x axis labels. Defaults to colnames(your_SE).
`n_clones` | The top 'n' clones to plot.
`cellnote_assay` | Character. One of "stars", "reads", "proportions" or "p_val"
`your_title` | The title for the plot.
`grid` | Logical. Include a grid or not in the heatmap.
`label_size` | The size of the column labels.
`dendro` | Logical. Whether or not to show row dendrogram when hierarchical clustering.
`cellnote_size` | The numerical size of the cell note labels.
`distance_method` | Character. Use summary(proxy::pr_DB) to see all possible options for distance metrics in clustering.
`minkowski_power` | The power of the Minkowski distance (if minkowski is the distance method used).
`hclust_linkage` | Character. One of "ward.D", "ward.D2", "single", "complete", "average" (= UPGMA), "mcquitty" (= WPGMA), "median" (= WPGMC) or "centroid" (= UPGMC).
`row_order` | Character; "hierarchical" to perform hierarchical clustering on the output and order in that manner, "emergence" to organize rows by order of presence in data (from left to right), or a character vector of rows within the summarized experiment to plot.
`clusters` | How many clusters to cut hierarchical tree into for display when row_order is "hierarchical".
`percent_scale` | A numeric vector through which to spread the color scale (values inclusive from 0 to 1). Must be same length as color_scale.
`color_scale` | A character vector which indicates the colors of the color scale. Must be same length as percent_scale.
`return_table` | Logical. Whether or not to return table of barcode sequences with their log abundance in the 'value' column and cellnote (* indicating statistical signficant change, for example) for each sample instead of displaying a plot. Note, for more in-depth statistical analysis, use the '"barcode_stat_test' function.

### Value

Displays a heatmap in the current plot window. Or if return_table is set to TRUE, returns a dataframe of the barcode sequences, log abundances, and cellnote for each sample.

### Examples

    data(wu_subset)
    barcode_ggheatmap_stat(
        your_SE = wu_subset[, 1:4], sample_size = rep(5000, 4),
        stat_test = "chi-squared", stat_option = "subsequent",
        p_threshold = 0.05, n_clones = 10,
        cellnote_assay = "stars", bc_threshold = 0.005
    )

[Package barcodetrackR version 1.0.0 Index]