Galaxy | Tool Preview

Plot (version 4.0.4+galaxy0)
Seurat RDS, Seurat H5, Single Cell Experiment RDS, Loom or AnnData
Select RDS file(s) with Seurat object for input
Either FeaturePlot, RidgePlot, DimPlot, VlnPlot or DotPlot.
Vector of features to plot. Features can come from: an assay feature (e.g. a gene name - MS4A1), a column name from meta.data (e.g. mitochondrial percentage - percent.mito), a column name from a DimReduc object corresponding to the cell embedding values (e.g. the PC 1 scores - PC_1).
Dimensions to plot, must be a two-length numeric vector specifying x- and y-dimensions
Vector of cells to plot (default is all cells)
The two colors to form the gradient over. Provide as string vector with the first color corresponding to low values, the second to high. Also accepts a Brewer color scale or vector of colors.
Adjust point size for plotting
Boolean determining whether to plot cells in order of expression. Can be useful if cells expressing given feature are getting buried.
Vector of minimum cutoff values for each feature, may specify quantile in the form of 'q##' where '##' is the quantile (eg, 'q1', 'q10')
Vector of maximum cutoff values for each feature, may specify quantile in the form of 'q##' where '##' is the quantile (eg, 'q1', 'q10')
Which dimensionality reduction to use. If not specified, first searches for umap, then tsne, then pca
A factor in object metadata to split the feature plot by, pass ident to split by cell identity; similar to the old FeatureHeatmap.
How to handle the color scale across multiple plots.
If NULL, all points are circles (default). You can specify any cell attribute (that can be pulled with FetchData) allowing for both different colors and different shapes on cells. Only applicable if 'raster' is FALSE) .
Which slot to pull expression data from?
Scale and blend expression values to visualize coexpression of two features
The color cutoff from weak signal to strong signal; ranges from 0 to 1.
Whether to label the clusters
Sets size of labels
Repel labels
Number of columns to combine multiple feature plots to, ignored if split.by is not NULL
Plot cartesian coordinates with fixed aspect ratio
If splitting by a factor, plot the splits per column with the features as rows; ignored if blend = TRUE.
Format to use, either PNG, EPS, PostScript, TeX, PDF, JPEG, TIFF or SVG
Units for the plot dimensions.
Plot resolution. Also accepts a string input: retina (320), print (300), or screen (72). Applies only to raster output types.
When TRUE (the default) ggsave() will not save images larger than 50x50 inches, to prevent the common error of specifying dimensions in pixels.
Background colour. If NULL, uses the plot.background fill value from the plot theme.
Enable output output_rds_file

What it does

Seurat_ is a toolkit for quality control, analysis, and exploration of single cell RNA sequencing data. It is developed and maintained by the `Satija Lab`_ at NYGC. Seurat aims to enable users to identify and interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse types of single cell data.

This tool produces the different plots available on Seurat.

Inputs

All the rest of the parameters are optional.

Outputs

Version history 4.0.0: Moves to Seurat 4.0.0, introducing a number of methods for merging datasets, plus the whole suite of Seurat plots. Pablo Moreno with funding from AstraZeneca.

3.2.3+galaxy0: Moves to Seurat 3.2.3 and introduce convert method, improving format interconversion support.

3.1.2_0.0.8: Update metadata parsing

3.1.1_0.0.7: Exposes perplexity and enables tab input.

3.1.1_0.0.6+galaxy0: Moved to Seurat 3.

Find clusters: removed dims-use, k-param, prune-snn.

2.3.1+galaxy0: Improved documentation and further exposition of all script's options. Pablo Moreno, Jonathan Manning and Ni Huang, Expression Atlas team https://www.ebi.ac.uk/gxa/home at EMBL-EBI https://www.ebi.ac.uk/. Parts obtained from wrappers from Christophe Antoniewski (GitHub drosofff) and Lea Bellenger (GitHub bellenger-l).

0.0.1: Initial contribution. Maria Doyle (GitHub mblue9).