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PieParty: visualizing cells from scRNA-seq data as pie charts
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 ex...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Life Science Alliance LLC
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8008964/ https://www.ncbi.nlm.nih.gov/pubmed/33674364 http://dx.doi.org/10.26508/lsa.202000986 |
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author | Kurtenbach, Stefan Dollar, James J Cruz, Anthony M Durante, Michael A Decatur, Christina L Harbour, J William |
author_facet | Kurtenbach, Stefan Dollar, James J Cruz, Anthony M Durante, Michael A Decatur, Christina L Harbour, J William |
author_sort | Kurtenbach, Stefan |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8008964 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Life Science Alliance LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-80089642021-04-02 PieParty: visualizing cells from scRNA-seq data as pie charts Kurtenbach, Stefan Dollar, James J Cruz, Anthony M Durante, Michael A Decatur, Christina L Harbour, J William Life Sci Alliance Research Articles 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. Life Science Alliance LLC 2021-03-05 /pmc/articles/PMC8008964/ /pubmed/33674364 http://dx.doi.org/10.26508/lsa.202000986 Text en © 2021 Stefan et al. https://creativecommons.org/licenses/by/4.0/This article is available under a Creative Commons License (Attribution 4.0 International, as described at https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Research Articles Kurtenbach, Stefan Dollar, James J Cruz, Anthony M Durante, Michael A Decatur, Christina L Harbour, J William PieParty: visualizing cells from scRNA-seq data as pie charts |
title | PieParty: visualizing cells from scRNA-seq data as pie charts |
title_full | PieParty: visualizing cells from scRNA-seq data as pie charts |
title_fullStr | PieParty: visualizing cells from scRNA-seq data as pie charts |
title_full_unstemmed | PieParty: visualizing cells from scRNA-seq data as pie charts |
title_short | PieParty: visualizing cells from scRNA-seq data as pie charts |
title_sort | pieparty: visualizing cells from scrna-seq data as pie charts |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8008964/ https://www.ncbi.nlm.nih.gov/pubmed/33674364 http://dx.doi.org/10.26508/lsa.202000986 |
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