CellexalVR : A virtual reality platform to visualize and analyze single-cell omics data
(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
- Legetth, Oscar LU ; Rodhe, Johan LU ; Lang, Stefan LU ; Dhapola, Parashar LU ; Wallergård, Mattias LU and Soneji, Shamit LU
- organization
- publishing date
- 2021-11
- 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
- 2024-09-08 06:11:13
@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}}, }