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    <h1>Waterfall Plot</h1>
    
    <div class="hidden name"><code>WaterfallPlot.Rd</code></div>
    </div>

    <div class="ref-description">
    <p>Generates a waterfall plot.</p>
    </div>

    <div id="ref-usage">
    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">WaterfallPlot</span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span><span class="op">)</span></span>
<span></span>
<span><span class="co"># S3 method for Seurat</span></span>
<span><span class="fu">WaterfallPlot</span><span class="op">(</span></span>
<span>  <span class="va">seu</span>,</span>
<span>  <span class="va">features</span>,</span>
<span>  group.by <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span>  cell <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span>  slot <span class="op">=</span> <span class="st">"data"</span>,</span>
<span>  assay <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span>  priority <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"expr"</span>, <span class="st">"none"</span><span class="op">)</span>,</span>
<span>  ident.1 <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span>  ident.2 <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span>  exp.transform <span class="op">=</span> <span class="op">(</span><span class="va">length</span> <span class="op">==</span> <span class="st">"logFC"</span><span class="op">)</span>,</span>
<span>  order <span class="op">=</span> <span class="cn">TRUE</span>,</span>
<span>  length <span class="op">=</span> <span class="st">"logFC"</span>,</span>
<span>  color <span class="op">=</span> <span class="st">"p"</span>,</span>
<span>  len.threshold <span class="op">=</span> <span class="fl">0</span>,</span>
<span>  col.threshold <span class="op">=</span> <span class="fl">0</span>,</span>
<span>  color_theme <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>low <span class="op">=</span> <span class="fu">muted</span><span class="op">(</span><span class="st">"blue"</span><span class="op">)</span>, mid <span class="op">=</span> <span class="st">"white"</span>, high <span class="op">=</span> <span class="fu">muted</span><span class="op">(</span><span class="st">"red"</span><span class="op">)</span><span class="op">)</span>,</span>
<span>  top.n <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span>  flip <span class="op">=</span> <span class="cn">FALSE</span>,</span>
<span>  y.label <span class="op">=</span> <span class="va">length</span>,</span>
<span>  angle <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span>  hjust <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span>  vjust <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span>  title <span class="op">=</span> <span class="cn">NULL</span></span>
<span><span class="op">)</span></span>
<span></span>
<span><span class="co"># S3 method for default</span></span>
<span><span class="fu">WaterfallPlot</span><span class="op">(</span></span>
<span>  <span class="va">matr</span>,</span>
<span>  <span class="va">f</span>,</span>
<span>  ident.1 <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span>  ident.2 <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span>  exp.transform <span class="op">=</span> <span class="cn">FALSE</span>,</span>
<span>  order <span class="op">=</span> <span class="cn">TRUE</span>,</span>
<span>  length <span class="op">=</span> <span class="st">"tscore"</span>,</span>
<span>  color <span class="op">=</span> <span class="st">"tscore"</span>,</span>
<span>  len.threshold <span class="op">=</span> <span class="fl">0</span>,</span>
<span>  col.threshold <span class="op">=</span> <span class="fl">0</span>,</span>
<span>  color_theme <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>low <span class="op">=</span> <span class="fu">muted</span><span class="op">(</span><span class="st">"blue"</span><span class="op">)</span>, mid <span class="op">=</span> <span class="st">"white"</span>, high <span class="op">=</span> <span class="fu">muted</span><span class="op">(</span><span class="st">"red"</span><span class="op">)</span><span class="op">)</span>,</span>
<span>  top.n <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span>  flip <span class="op">=</span> <span class="cn">TRUE</span>,</span>
<span>  y.label <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span>  angle <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span>  hjust <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span>  vjust <span class="op">=</span> <span class="cn">NULL</span>,</span>
<span>  title <span class="op">=</span> <span class="cn">NULL</span></span>
<span><span class="op">)</span></span></code></pre></div>
    </div>

    <div id="arguments">
    <h2>Arguments</h2>
    <dl><dt>object</dt>
<dd><p>Either a Seurat object or a matrix.</p></dd>


<dt>...</dt>
<dd><p>Additional arguments passed to other methods.</p></dd>


<dt>seu</dt>
<dd><p>A Seurat object. Only applicable when using the Seurat method.</p></dd>


<dt>features</dt>
<dd><p>Features to be plotted, which can include gene expression, metrics, PC scores, or any other data that can be retrieved using the `FetchData()` function. Only applicable for the Seurat method.</p></dd>


<dt>group.by</dt>
<dd><p>A variable from `meta.data` for grouping, or a character vector of the same length as the number of cells. Only applicable for the Seurat method.</p></dd>


<dt>cell</dt>
<dd><p>Cell identifiers to be used in the plot. Defaults to all cells. Only applicable for the Seurat method.</p></dd>


<dt>slot</dt>
<dd><p>Slot from which to retrieve feature data. Only applicable for the Seurat method.</p></dd>


<dt>assay</dt>
<dd><p>Name of the assay to use. If not specified, the active assay will be used. Only applicable for the Seurat method.</p></dd>


<dt>priority</dt>
<dd><p>If set to "expr", the function will fetch data from the expression matrix rather than `meta.data`. Only applicable for the Seurat method.</p></dd>


<dt>ident.1</dt>
<dd><p>The primary identity class. If not specified, the first class will be used.</p></dd>


<dt>ident.2</dt>
<dd><p>An optional secondary identity class for comparison. If NULL, comparisons will be made against all other cells.</p></dd>


<dt>exp.transform</dt>
<dd><p>Indicates whether to transform data using `expm1`. This is particularly useful when calculating the log fold change of normalized gene counts. Defaults to FALSE for matrix input and TRUE for Seurat object input.</p></dd>


<dt>order</dt>
<dd><p>Determines whether the features should be ordered. Defaults to TRUE.</p></dd>


<dt>length</dt>
<dd><p>Specifies the statistic to determine the length of the bar. Possible values are "tscore" (default for matrix input), "p", or "logFC" (default for Seurat object input).</p></dd>


<dt>color</dt>
<dd><p>Specifies the statistic to determine the color of the bar. Possible values are "tscore" (default), "p" (default for Seurat object input), or "logFC".</p></dd>


<dt>len.threshold</dt>
<dd><p>Excludes features with a value for the `length` parameter below this threshold. Defaults to 0.</p></dd>


<dt>col.threshold</dt>
<dd><p>Excludes features with a value for the `color` parameter below this threshold. Defaults to 0.</p></dd>


<dt>top.n</dt>
<dd><p>Retains only the top `n` bars in both positive and negative directions. If `length(top.n)` is 1, the function retains `top.n` bars for both positive and negative directions. If `length(top.n)` is 2, it retains `top.n[1]` positive bars and `top.n[2]` negative bars. Defaults to NULL.</p></dd>


<dt>flip</dt>
<dd><p>Determines whether the plot should be flipped. Defaults to TRUE for matrix input and FALSE for Seurat object input.</p></dd>


<dt>y.label</dt>
<dd><p>Label for the y-axis. Defaults to "length".</p></dd>


<dt>angle</dt>
<dd><p>Angle of the x-axis labels. This argument is passed to `element_text()`.</p></dd>


<dt>hjust</dt>
<dd><p>Horizontal justification for the x-axis labels. This argument is passed to `element_text()`.</p></dd>


<dt>vjust</dt>
<dd><p>Vertical justification for the x-axis labels. This argument is passed to `element_text()`.</p></dd>


<dt>title</dt>
<dd><p>Title of the plot. Defaults to NULL.</p></dd>


<dt>matr</dt>
<dd><p>A matrix or data frame where rows represent features and columns represent cells.</p></dd>


<dt>f</dt>
<dd><p>A factor or vector indicating the identity of each cell. The length should match the number of columns in `matr`.</p></dd>


<dt>color_scheme</dt>
<dd><p>Specifies the color gradient for the heatmap visualization.
  This parameter accepts multiple input formats to provide flexibility in defining color schemes:</p>
<p>- Predefined color schemes: Users can specify "A", "B", "C", "D", or "E" to use color schemes from the `viridis` package.</p>
<p>- Named vector for three-point gradients: Provide a named vector with keys "low", "mid", and "high" to define colors at these specific data points. The "mid" value is typically centered at zero, allowing for a diverging color scheme.
    Example: `c(low = "blue", mid = "white", high = "red")`</p>
<p>- Two-point gradient: Provide a named vector with keys "low" and "high" to create a simple two-color gradient. Example: `c(low = "blue", high = "red")`</p>
<p>- Custom color gradient: Users can provide a vector of colors to generate a custom gradient across multiple values. This is suitable for more complex data ranges and visual preferences.</p></dd>

</dl></div>
    <div id="value">
    <h2>Value</h2>
    

<p>A ggplot object.</p>
    </div>
    <div id="details">
    <h2>Details</h2>
    <p>For more detailed usage, see the examples provided.</p>
    </div>

    <div id="ref-examples">
    <h2>Examples</h2>
    <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="co"># First, create a matrix using the GeneSetAnalysis() function.</span></span>
<span><span class="co"># Rows represent the Hallmark 50 genesets, and columns represent cells.</span></span>
<span><span class="va">pbmc</span> <span class="op">&lt;-</span> <span class="fu"><a href="GeneSetAnalysis.html">GeneSetAnalysis</a></span><span class="op">(</span><span class="va">pbmc</span>, genesets <span class="op">=</span> <span class="va">hall50</span><span class="op">$</span><span class="va">human</span><span class="op">)</span></span>
<span><span class="va">matr</span> <span class="op">&lt;-</span> <span class="va">pbmc</span><span class="op">@</span><span class="va">misc</span><span class="op">$</span><span class="va">AUCell</span><span class="op">$</span><span class="va">genesets</span></span>
<span></span>
<span><span class="co"># Generate a waterfall plot comparing CD14+ Mono with CD8 T cells.</span></span>
<span><span class="fu">WaterfallPlot</span><span class="op">(</span><span class="va">matr</span>, f <span class="op">=</span> <span class="va">pbmc</span><span class="op">$</span><span class="va">cluster</span>, ident.1 <span class="op">=</span> <span class="st">"Mono CD14"</span>, ident.2 <span class="op">=</span> <span class="st">"CD8 T cell"</span><span class="op">)</span></span>
<span></span>
<span><span class="co"># Keep only bars with a length (tscore, in this instance) greater than 1.</span></span>
<span><span class="fu">WaterfallPlot</span><span class="op">(</span><span class="va">matr</span>, f <span class="op">=</span> <span class="va">pbmc</span><span class="op">$</span><span class="va">cluster</span>, ident.1 <span class="op">=</span> <span class="st">"Mono CD14"</span>, ident.2 <span class="op">=</span> <span class="st">"CD8 T cell"</span>, len.threshold <span class="op">=</span> <span class="fl">1</span><span class="op">)</span></span>
<span></span>
<span><span class="co"># Use a Seurat object as input and compare 100 genes, using LogFC as bar length.</span></span>
<span><span class="va">genes</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://mojaveazure.github.io/seurat-object/reference/VariableFeatures.html" class="external-link">VariableFeatures</a></span><span class="op">(</span><span class="va">pbmc</span><span class="op">)</span><span class="op">[</span><span class="fl">1</span><span class="op">:</span><span class="fl">80</span><span class="op">]</span></span>
<span><span class="fu">WaterfallPlot</span><span class="op">(</span></span>
<span>  <span class="va">pbmc</span>, group.by <span class="op">=</span> <span class="st">"cluster"</span>, features <span class="op">=</span> <span class="va">genes</span>,</span>
<span>  ident.1 <span class="op">=</span> <span class="st">"Mono CD14"</span>, ident.2 <span class="op">=</span> <span class="st">"CD8 T cell"</span>, length <span class="op">=</span> <span class="st">"logFC"</span><span class="op">)</span></span>
<span></span>
<span><span class="co"># Keep only the top and bottom 20 genes.</span></span>
<span><span class="fu">WaterfallPlot</span><span class="op">(</span></span>
<span>  <span class="va">pbmc</span>, group.by <span class="op">=</span> <span class="st">"cluster"</span>, features <span class="op">=</span> <span class="va">genes</span>,</span>
<span>  ident.1 <span class="op">=</span> <span class="st">"Mono CD14"</span>, ident.2 <span class="op">=</span> <span class="st">"CD8 T cell"</span>, length <span class="op">=</span> <span class="st">"logFC"</span>,</span>
<span>  top.n <span class="op">=</span> <span class="fl">20</span><span class="op">)</span></span></code></pre></div>
    </div>
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