Single-cell RNA sequencing of pleomorphic rhabdomyosarcoma
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| Formato: | Recurso digital |
| Lenguaje: | inglés |
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2025
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| _version_ | 1866902322808881152 |
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| author | Ikonnikov, Alexandr |
| author_facet | Ikonnikov, Alexandr |
| contents | <p><strong>Single-Cell RNA Sequencing Quality Control and Data Processing<br><br></strong>Demultiplexing of the scRNA-seq data was done using the Cell Ranger 7.1.0 (10x Genomics, USA) pipeline. The data was aligned to the GRCh38-2020-A reference genome.</p> <p><strong>Sample Preparation for Single-Cell RNA Sequencing</strong></p> <p>The pRMS tumor sample of 20-25 mg was excised. The tumor samples were placed into the Fixation buffer (10x Genomics, USA) immediately after excision. The fixation and dissociation of the sample was performed according to the Tissue Fixation & Dissociation Protocol for Chromium Fixed RNA Profiling (10x Genomics, USA). The cells were counted using an acridine orange/propidium iodide stain buffer (Logos Bioscience, Korea) on LUNA-FL Dual Fluorescence Cell Counter (Logos Bioscience, Korea). The cell suspension was stored at –80℃ with 100 μ l of Enhancer solution (10x Genomics, USA) and 275 μ l of 50% glycerol. Before the Chromium Fixed RNA Profiling experiment, the cells were thawed, centrifuged, resuspended in 0.5x PBS with 0.02% BSA, and counted again. 8000 cells were taken into the scRNA-seq experiment.</p> <p><strong>Single-Cell RNA Library Construction and Sequencing</strong></p> <p>The scRNA-seq libraries were made according to the Chromium Fixed RNA Protocol (10x Genomics, USA). The GEM particles were generated on Chromium iX/X (10x Genomics, USA). The amplification steps were performed on the RT-PCR machine QuantGene 9600 (Bioer, China). The scRNA-seq libraries were sequenced on the Genolab M platform (Genemind, China) with the following program: 28 cycles for read 1 and 90 cycles for read 2.430</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_17349024 |
| institution | Zenodo |
| language | eng |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Single-cell RNA sequencing of pleomorphic rhabdomyosarcoma Ikonnikov, Alexandr Single-Cell Analysis Single-Cell Gene Expression Analysis Single-Cell Analysis/statistics & numerical data <p><strong>Single-Cell RNA Sequencing Quality Control and Data Processing<br><br></strong>Demultiplexing of the scRNA-seq data was done using the Cell Ranger 7.1.0 (10x Genomics, USA) pipeline. The data was aligned to the GRCh38-2020-A reference genome.</p> <p><strong>Sample Preparation for Single-Cell RNA Sequencing</strong></p> <p>The pRMS tumor sample of 20-25 mg was excised. The tumor samples were placed into the Fixation buffer (10x Genomics, USA) immediately after excision. The fixation and dissociation of the sample was performed according to the Tissue Fixation & Dissociation Protocol for Chromium Fixed RNA Profiling (10x Genomics, USA). The cells were counted using an acridine orange/propidium iodide stain buffer (Logos Bioscience, Korea) on LUNA-FL Dual Fluorescence Cell Counter (Logos Bioscience, Korea). The cell suspension was stored at –80℃ with 100 μ l of Enhancer solution (10x Genomics, USA) and 275 μ l of 50% glycerol. Before the Chromium Fixed RNA Profiling experiment, the cells were thawed, centrifuged, resuspended in 0.5x PBS with 0.02% BSA, and counted again. 8000 cells were taken into the scRNA-seq experiment.</p> <p><strong>Single-Cell RNA Library Construction and Sequencing</strong></p> <p>The scRNA-seq libraries were made according to the Chromium Fixed RNA Protocol (10x Genomics, USA). The GEM particles were generated on Chromium iX/X (10x Genomics, USA). The amplification steps were performed on the RT-PCR machine QuantGene 9600 (Bioer, China). The scRNA-seq libraries were sequenced on the Genolab M platform (Genemind, China) with the following program: 28 cycles for read 1 and 90 cycles for read 2.430</p> |
| title | Single-cell RNA sequencing of pleomorphic rhabdomyosarcoma |
| topic | Single-Cell Analysis Single-Cell Gene Expression Analysis Single-Cell Analysis/statistics & numerical data |
| url | https://doi.org/10.5281/zenodo.17349024 |