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singlecellVR: Interactive Visualization of Single-Cell Data in Virtual Reality
Single-cell assays have transformed our ability to model heterogeneity within cell populations. As these assays have advanced in their ability to measure various aspects of molecular processes in cells, computational methods to analyze and meaningfully visualize such data have required matched innov...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8582280/ https://www.ncbi.nlm.nih.gov/pubmed/34777482 http://dx.doi.org/10.3389/fgene.2021.764170 |
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author | Stein, David F. Chen, Huidong Vinyard, Michael E. Qin, Qian Combs, Rebecca D. Zhang, Qian Pinello, Luca |
author_facet | Stein, David F. Chen, Huidong Vinyard, Michael E. Qin, Qian Combs, Rebecca D. Zhang, Qian Pinello, Luca |
author_sort | Stein, David F. |
collection | PubMed |
description | Single-cell assays have transformed our ability to model heterogeneity within cell populations. As these assays have advanced in their ability to measure various aspects of molecular processes in cells, computational methods to analyze and meaningfully visualize such data have required matched innovation. Independently, Virtual Reality (VR) has recently emerged as a powerful technology to dynamically explore complex data and shows promise for adaptation to challenges in single-cell data visualization. However, adopting VR for single-cell data visualization has thus far been hindered by expensive prerequisite hardware or advanced data preprocessing skills. To address current shortcomings, we present singlecellVR, a user-friendly web application for visualizing single-cell data, designed for cheap and easily available virtual reality hardware (e.g., Google Cardboard, ∼$8). singlecellVR can visualize data from a variety of sequencing-based technologies including transcriptomic, epigenomic, and proteomic data as well as combinations thereof. Analysis modalities supported include approaches to clustering as well as trajectory inference and visualization of dynamical changes discovered through modelling RNA velocity. We provide a companion software package, scvr to streamline data conversion from the most widely-adopted single-cell analysis tools as well as a growing database of pre-analyzed datasets to which users can contribute. |
format | Online Article Text |
id | pubmed-8582280 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-85822802021-11-12 singlecellVR: Interactive Visualization of Single-Cell Data in Virtual Reality Stein, David F. Chen, Huidong Vinyard, Michael E. Qin, Qian Combs, Rebecca D. Zhang, Qian Pinello, Luca Front Genet Genetics Single-cell assays have transformed our ability to model heterogeneity within cell populations. As these assays have advanced in their ability to measure various aspects of molecular processes in cells, computational methods to analyze and meaningfully visualize such data have required matched innovation. Independently, Virtual Reality (VR) has recently emerged as a powerful technology to dynamically explore complex data and shows promise for adaptation to challenges in single-cell data visualization. However, adopting VR for single-cell data visualization has thus far been hindered by expensive prerequisite hardware or advanced data preprocessing skills. To address current shortcomings, we present singlecellVR, a user-friendly web application for visualizing single-cell data, designed for cheap and easily available virtual reality hardware (e.g., Google Cardboard, ∼$8). singlecellVR can visualize data from a variety of sequencing-based technologies including transcriptomic, epigenomic, and proteomic data as well as combinations thereof. Analysis modalities supported include approaches to clustering as well as trajectory inference and visualization of dynamical changes discovered through modelling RNA velocity. We provide a companion software package, scvr to streamline data conversion from the most widely-adopted single-cell analysis tools as well as a growing database of pre-analyzed datasets to which users can contribute. Frontiers Media S.A. 2021-10-28 /pmc/articles/PMC8582280/ /pubmed/34777482 http://dx.doi.org/10.3389/fgene.2021.764170 Text en Copyright © 2021 Stein, Chen, Vinyard, Qin, Combs, Zhang and Pinello. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Stein, David F. Chen, Huidong Vinyard, Michael E. Qin, Qian Combs, Rebecca D. Zhang, Qian Pinello, Luca singlecellVR: Interactive Visualization of Single-Cell Data in Virtual Reality |
title | singlecellVR: Interactive Visualization of Single-Cell Data in Virtual Reality |
title_full | singlecellVR: Interactive Visualization of Single-Cell Data in Virtual Reality |
title_fullStr | singlecellVR: Interactive Visualization of Single-Cell Data in Virtual Reality |
title_full_unstemmed | singlecellVR: Interactive Visualization of Single-Cell Data in Virtual Reality |
title_short | singlecellVR: Interactive Visualization of Single-Cell Data in Virtual Reality |
title_sort | singlecellvr: interactive visualization of single-cell data in virtual reality |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8582280/ https://www.ncbi.nlm.nih.gov/pubmed/34777482 http://dx.doi.org/10.3389/fgene.2021.764170 |
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