PieParty: visualizing cells from scRNA-seq data as pie charts.
Stefan KurtenbachJames J DollarAnthony M CruzMichael A DuranteChristina L DecaturJ William HarbourPublished in: Life science alliance (2021)
Single-cell RNA sequencing (scRNA-seq) has been a transformative technology in many research fields. Dimensional reduction techniques such as UMAP and tSNE are used to visualize scRNA-seq data in two or three dimensions for cells to be clustered in biologically meaningful ways. Subsequently, gene expression is frequently mapped onto these plots to show the distribution of gene expression across the plots, for instance to distinguish cell types. However, plotting each cell with only a single color leads to repetitive and unintuitive representations. Here, we present PieParty, which allows scRNA-seq data to be plotted such that every cell is represented as a pie chart, and every slice in the pie charts corresponds to the gene expression of a single gene. This allows for the simultaneous visualization of the expression of multiple genes and gene networks. The resulting figures are information dense, space efficient, and highly intuitive. PieParty is publicly available on GitHub at https://github.com/harbourlab/PieParty.
Keyphrases
- single cell
- gene expression
- rna seq
- genome wide
- dna methylation
- high throughput
- electronic health record
- big data
- healthcare
- stem cells
- induced apoptosis
- working memory
- poor prognosis
- genome wide identification
- cell therapy
- computed tomography
- oxidative stress
- high frequency
- mesenchymal stem cells
- health information
- binding protein
- data analysis