<i>singlecellVR</i>: interactive visualization of single-cell data in virtual reality

Stein, David; Chen, Huidong; Vinyard, Michael; Pinello, Luca

doi:10.1101/2020.07.30.229534

Cited by 4 publications

(3 citation statements)

References 43 publications

(101 reference statements)

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“…There are currently three other projects in preprint that allow users to visualize single-cell data in stereoscopic 3D, starmapvr ( Yang et al., 2018 ), singlecellvr ( Stein et al., 2020 ), and Theia ( Bressan et al, 2021 ) (which will also handle spatial data). Both starmapvr and single-cellvr utilize Google cardboard where a mobile phone is placed inside a visor to form a rudimentary 3D viewer.…”

Section: Resultsmentioning

confidence: 99%

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

et al. 2021

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Section: Resultsmentioning

confidence: 99%

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

et al. 2021

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Section: Methodsmentioning

confidence: 99%

“…Data were visualized using custom Python scripts (v3.7.1) in Jupyter Notebooks (v6.1.4), GraphPad Prism (v8) and scanpy (v1.6) (53). Scanpy was also used to prepare data for visualization in virtual reality using the singlecellVR website (singlecellvr.com) (54). siRNA RPE cells were treated with DMSO or etoposide (1 μM) for 24h then transfected with non-targeting (Dharmacon, D-001810-10-0) or cyclin D1/D2/D3 (SMARTPools L-003210-00-0005/L-003211-00-0005/L-003212-00-0005) siRNA pools using the DharmaFECT 1 transfection reagent (T-2001-01) as per manufacturer's protocol and incubated for 3 days prior to fixation.…”

Section: Random Forest Modelsmentioning

confidence: 99%

The structure of the human cell cycle

Stallaert

Kedziora

Taylor

et al. 2021

Preprint

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The human cell cycle is conventionally depicted as a five-phase model consisting of four proliferative phases (G1, S, G2, M) and a single state of arrest (G0). However, recent studies show that individual cells can take different paths through the cell cycle and exit into distinct arrest states, thus necessitating an update to the canonical model. We combined time lapse microscopy, highly multiplexed single cell imaging and manifold learning to determine the underlying structure of the human cell cycle under multiple growth and arrest conditions. By visualizing the cell cycle as a complete biological process, we identified multiple points of divergence from the proliferative cell cycle into distinct states of arrest, revealing multiple mechanisms of cell cycle exit and re-entry and the molecular routes to senescence, endoreduplication and polyploidy. These findings enable the visualization and comparison of alternative cell cycles in development and disease.

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EpiScanpy: integrated single-cell epigenomic analysis

et al. 2021

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EpiScanpy is a toolkit for the analysis of single-cell epigenomic data, namely single-cell DNA methylation and single-cell ATAC-seq data. To address the modality specific challenges from epigenomics data, epiScanpy quantifies the epigenome using multiple feature space constructions and builds a nearest neighbour graph using epigenomic distance between cells. EpiScanpy makes the many existing scRNA-seq workflows from scanpy available to large-scale single-cell data from other -omics modalities, including methods for common clustering, dimension reduction, cell type identification and trajectory learning techniques, as well as an atlas integration tool for scATAC-seq datasets. The toolkit also features numerous useful downstream functions, such as differential methylation and differential openness calling, mapping epigenomic features of interest to their nearest gene, or constructing gene activity matrices using chromatin openness. We successfully benchmark epiScanpy against other scATAC-seq analysis tools and show its outperformance at discriminating cell types.

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singlecellVR: interactive visualization of single-cell data in virtual reality

Cited by 4 publications

References 43 publications

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

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

The structure of the human cell cycle

EpiScanpy: integrated single-cell epigenomic analysis

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