RT Journal Article
SR Electronic
T1 PieParty: visualizing cells from scRNA-seq data as pie charts
JF Life Science Alliance
JO Life Sci. Alliance
FD Life Science Alliance LLC
SP e202000986
DO 10.26508/lsa.202000986
VO 4
IS 5
A1 Kurtenbach, Stefan
A1 Dollar, James J
A1 Cruz, Anthony M
A1 Durante, Michael A
A1 Decatur, Christina L
A1 Harbour, J William
YR 2021
UL http://www.life-science-alliance.org/content/4/5/e202000986.abstract
AB 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.