Assessing the reliability of spike-in normalization for analyses of single-cell RNA sequencing data.
Cold Spring Harbor Laboratory Press
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Lun, A., Calero-Nieto, F. J., Haim-Vilmovsky, L., Gottgens, B., & Marioni, J. (2017). Assessing the reliability of spike-in normalization for analyses of single-cell RNA sequencing data.. Genome research, 27 (11), 1795-1806. https://doi.org/10.1101/gr.222877.117
By pro ling the transcriptomes of individual cells, single-cell RNA sequencing provides unparalleled resolution to study cellular heterogeneity. However, this comes at the cost of high technical noise, including cell-spec c biases in capture efficiency and library generation. One strategy for removing these biases is to add a constant amount of spikein RNA to each cell, and to scale the observed expression values so that the coverage of spike-in transcripts is constant across cells. This approach has previously been criticized as its accuracy depends on the precise addition of spike-in RNA to each sample. Here, we perform mixture experiments using two di erent sets of spike-in RNA to quantify the variance in the amount of spike-in RNA added to each well in a plate-based protocol. We also obtain an upper bound on the variance due to di erences in behaviour between the two spike-in sets. We demonstrate that both factors are small contributors to the total technical variance and have only minor e ects on downstream analyses such as detection of highly variable genes and clustering. Our results suggest that scaling normalization using spike-in transcripts is reliable enough for routine use in single-cell RNA sequencing data analyses.
Cell Line, Animals, Mice, Reproducibility of Results, Gene Expression Profiling, Sequence Analysis, RNA, Gene Expression Regulation, Algorithms, Single-Cell Analysis
This work was supported by Cancer Research UK (core funding to JCM, award no. A17197), the University of Cambridge and Hutchison Whampoa Limited. JCM was also supported by core funding from EMBL. LHV was supported by an EMBL Interdisciplinary Postdoctoral fellowship. Work in the G ottgens group was supported by Cancer Research UK, Bloodwise, the National Institute of Diabetes and Digestive and Kidney Diseases, the Leukemia and Lymphoma Society and core infrastructure grants from the Wellcome Trust and the Medical Research Council to the Cambridge Stem Cell Institute.
Cancer Research UK (C14303_do not transfer)
Cancer Research UK (21762)
Leukaemia & Lymphoma Research (12029)
MEDICAL RESEARCH COUNCIL (MR/M008975/1)
National Institutes of Health (NIH) (via Pennsylvania State University) (R24DK106766)
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External DOI: https://doi.org/10.1101/gr.222877.117
This record's URL: https://www.repository.cam.ac.uk/handle/1810/274788
Attribution 4.0 International
Licence URL: http://creativecommons.org/licenses/by/4.0/
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