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CellexalVR : A virtual reality platform to visualize and analyze single-cell omics data

Legetth, Oscar LU ; Rodhe, Johan LU ; Lang, Stefan LU orcid ; Dhapola, Parashar LU ; Wallergård, Mattias LU and Soneji, Shamit LU (2021) In iScience 24(11).
Abstract

Single-cell RNAseq is a routinely used method to explore heterogeneity within cell populations. Data from these experiments are often visualized using dimension reduction methods such as UMAP and tSNE, where each cell is projected in two or three dimensional space. Three-dimensional projections can be more informative for larger and complex datasets because they are less prone to merging and flattening similar cell-types/clusters together. However, visualizing and cross-comparing 3D projections using current software on conventional flat-screen displays is far from optimal as they are still essentially 2D, and lack meaningful interaction between the user and the data. Here we present CellexalVR (www.cellexalvr.med.lu.se), a... (More)

Single-cell RNAseq is a routinely used method to explore heterogeneity within cell populations. Data from these experiments are often visualized using dimension reduction methods such as UMAP and tSNE, where each cell is projected in two or three dimensional space. Three-dimensional projections can be more informative for larger and complex datasets because they are less prone to merging and flattening similar cell-types/clusters together. However, visualizing and cross-comparing 3D projections using current software on conventional flat-screen displays is far from optimal as they are still essentially 2D, and lack meaningful interaction between the user and the data. Here we present CellexalVR (www.cellexalvr.med.lu.se), a feature-rich, fully interactive virtual reality environment for the visualization and analysis of single-cell experiments that allows researchers to intuitively and collaboratively gain an understanding of their data.

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author
; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Bioinformatics, Computer science, Omics, Software engineering, Systems biology, Transcriptomics
in
iScience
volume
24
issue
11
article number
103251
publisher
Elsevier
external identifiers
  • pmid:34849461
  • scopus:85119320128
ISSN
2589-0042
DOI
10.1016/j.isci.2021.103251
language
English
LU publication?
yes
id
8ec8ab1d-db1f-4474-b838-1c03c96c1bfc
date added to LUP
2021-12-03 15:09:50
date last changed
2024-06-15 22:08:33
@article{8ec8ab1d-db1f-4474-b838-1c03c96c1bfc,
  abstract     = {{<p>Single-cell RNAseq is a routinely used method to explore heterogeneity within cell populations. Data from these experiments are often visualized using dimension reduction methods such as UMAP and tSNE, where each cell is projected in two or three dimensional space. Three-dimensional projections can be more informative for larger and complex datasets because they are less prone to merging and flattening similar cell-types/clusters together. However, visualizing and cross-comparing 3D projections using current software on conventional flat-screen displays is far from optimal as they are still essentially 2D, and lack meaningful interaction between the user and the data. Here we present CellexalVR (www.cellexalvr.med.lu.se), a feature-rich, fully interactive virtual reality environment for the visualization and analysis of single-cell experiments that allows researchers to intuitively and collaboratively gain an understanding of their data.</p>}},
  author       = {{Legetth, Oscar and Rodhe, Johan and Lang, Stefan and Dhapola, Parashar and Wallergård, Mattias and Soneji, Shamit}},
  issn         = {{2589-0042}},
  keywords     = {{Bioinformatics; Computer science; Omics; Software engineering; Systems biology; Transcriptomics}},
  language     = {{eng}},
  number       = {{11}},
  publisher    = {{Elsevier}},
  series       = {{iScience}},
  title        = {{CellexalVR : A virtual reality platform to visualize and analyze single-cell omics data}},
  url          = {{http://dx.doi.org/10.1016/j.isci.2021.103251}},
  doi          = {{10.1016/j.isci.2021.103251}},
  volume       = {{24}},
  year         = {{2021}},
}