Performance comparison of high throughput single-cell RNA-Seq platforms in complex tissues

Single-cell transcriptomics has emerged as the preferred tool to define cell identity through the analysis of gene expression signatures. However, there are limited studies that have comprehensively compared the performance of different scRNAseq systems in complex tissues. Here, we present a systematic comparison of two well-established high throughput 3'-scRNAseq platforms: 10× Chromium and BD Rhapsody, using tumours that present high cell diversity. Our experimental design includes both fresh and artificially damaged samples from the same tumours, which also provides a comparable dataset to examine their performance under challenging conditions. The performance metrics used in this study consist of gene sensitivity, mitochondrial content, reproducibility, clustering capabilities, cell type representation and ambient RNA contamination. These analyses showed that BD Rhapsody and 10× Chromium have similar gene sensitivity, while BD Rhapsody has the highest mitochondrial content. Interestingly, we found cell type detection biases between platforms, including a lower proportion of endothelial and myofibroblast cells in BD Rhapsody and lower gene sensitivity in granulocytes for 10× Chromium. Moreover, the source of the ambient noise was different between plate-based and droplet-based platforms. In conclusion, our reported platform differential performance should be considered for the selection of the scRNAseq method during the study experimental designs.

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Publication Details

Journal
Heliyon
Published
2024-08-30
DOI
https://doi.org/10.1016/j.heliyon.2024.e37185
Citations
12
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
2.81

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article

Performance comparison of high throughput single-cell RNA-Seq platforms in complex tissues

Andrew M. K. Law, Brian Gloss, David Gallego‐Ortega, Yolanda Colino‐Sanguino et al.
12 citations
Heliyon
Single-cell and spatial transcriptomics
2.81
article

Performance comparison of high throughput single-cell RNA-Seq platforms in complex tissues

Andrew M. K. Law, Brian Gloss, David Gallego‐Ortega, Yolanda Colino‐Sanguino, Fátima Valdés‐Mora, Robert Salomon, Kristina Handler, Marina Pajic, Laura Rodríguez de la Fuente
article en
12 citations

Abstract

Single-cell transcriptomics has emerged as the preferred tool to define cell identity through the analysis of gene expression signatures. However, there are limited studies that have comprehensively compared the performance of different scRNAseq systems in complex tissues. Here, we present a systematic comparison of two well-established high throughput 3'-scRNAseq platforms: 10× Chromium and BD Rhapsody, using tumours that present high cell diversity. Our experimental design includes both fresh and artificially damaged samples from the same tumours, which also provides a comparable dataset to examine their performance under challenging conditions. The performance metrics used in this study consist of gene sensitivity, mitochondrial content, reproducibility, clustering capabilities, cell type representation and ambient RNA contamination. These analyses showed that BD Rhapsody and 10× Chromium have similar gene sensitivity, while BD Rhapsody has the highest mitochondrial content. Interestingly, we found cell type detection biases between platforms, including a lower proportion of endothelial and myofibroblast cells in BD Rhapsody and lower gene sensitivity in granulocytes for 10× Chromium. Moreover, the source of the ambient noise was different between plate-based and droplet-based platforms. In conclusion, our reported platform differential performance should be considered for the selection of the scRNAseq method during the study experimental designs.

HeliyonVol. 10(17)
University of Technology Sydney (AU), Garvan Institute of Medical Research (AU), University of Zurich (CH), UNSW Sydney (AU), Children's Cancer Institute Australia (AU), Westmead Institute for Medical Research (AU), The Kinghorn Cancer Centre (AU)
National Breast Cancer Foundation, Cancer Institute NSW, Cure Brain Cancer Foundation, National Health and Medical Research Council, Cancer Council NSW
Openalex Percentile: Top 9%
Single-cell and spatial transcriptomics
2.81
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