Dot plot visualization — DotPlot • Seurat - Satija Lab
Intuitive way of visualizing how feature expression changes across different identity classes (clusters). The size of the dot encodes the percentage of cells within a class, while the color encodes the AverageExpression level across all cells within a class (blue is high).
How to make a multi-group dotplot for single-cell RNAseq data
Jan 16, 2024 · Dotplots are very popular for visualizing single-cell RNAseq data. In essence, the dot size represents the percentage of cells that are positive for that gene; the color intensity represents the average gene expression of that gene in a cell type.
Data visualization methods in Seurat - Satija Lab
This is done by passing the Seurat object used to make the plot into CellSelector(), as well as an identity class. As an example, we’re going to select the same set of cells as before, and set their identity class to “selected”
Tutorial: guidelines for annotating single-cell transcriptomic maps ...
May 24, 2021 · This tutorial provides guidelines for interpreting single-cell transcriptomic maps to identify cell types, states and other biologically relevant patterns.
clustered dotplot for single-cell RNAseq | Chatomics
Mar 10, 2021 · It gives information (by color) for the average expression level across cells within the cluster and the percentage (by size of the dot) of the cells express that gene within the cluster. Seurat has a nice function for that.
DotPlot: Dot plot visualization in Seurat: Tools for Single Cell …
May 29, 2024 · Dot plot visualization Description. Intuitive way of visualizing how feature expression changes across different identity classes (clusters). The size of the dot encodes the percentage of cells within a class, while the color encodes the AverageExpression level across all cells within a class (blue is high). Usage
scDotPlot - Bioconductor
Oct 29, 2024 · The scDotPlot package offers a unified approach to perform a hierarchical clustering analysis and add annotations to the columns and/or rows of a scRNA-seq dot plot. It works with SingleCellExperiment and Seurat objects as well as data frames.
Advanced plots — Asc-Seurat: Analytical single-cell Seurat …
Starting on v2.0, Asc-Seurat also provides the capacity of generating dot plots and “stacked violin plots” comparing multiple genes. Using an rds file containing the clustered data as input, users must provide a csv or tsv file in the same format described in the expression visualization section.
Apr 3, 2020 · Results: We developed FlexDotPlot, an R package for generating dot plots from any type of multifaceted data, including single- cell RNA-seq data. FlexDotPlot provides a universal and easy-to-use solution with a high versatility.
Expression visualization — Asc-Seurat: Analytical single-cell …
For each selected gene, Asc-Seurat will also generate plots to visualize the distribution of cells within each cluster according to the expression of the gene (violin plot) and the percentage of cells in each cluster expressing the gene (dot plot) in each sample.