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Published February 2020 | Supplemental Material + Submitted
Journal Article Open

Droplet scRNA-seq is not zero-inflated

Abstract

Potential users of single-cell RNA-sequencing (scRNA-seq) often encounter a choice between high-throughput droplet-based methods and high-sensitivity plate-based methods. There is a widespread belief that scRNA-seq will often fail to generate measurements for some genes from some cells owing to technical molecular inefficiencies. It is believed that this causes data to have an overabundance of zero values compared to what is expected from random sampling and that this effect is particularly pronounced in droplet-based methods. Here I present an investigation of published data for technical controls in droplet-based scRNA-seq experiments that demonstrates that the number of zero values in the data is consistent with common distributional models of molecule sampling counts. Thus, any additional zero values in biological data likely result from biological variation or may reflect variation in gene abundance among cell types or cell states.

Additional Information

© 2020 Springer Nature Limited. Published 14 January 2020. I thank E. da Veiga Beltrame for feedback on the manuscript, G. Eraslan for making fast code for fitting negative binomial models available, and the scientific community on Twitter for suggesting writing up this analysis as a manuscript. V.S. was funded in part by the EMBL International PhD Programme and NIH U19MH114830. The author declares no competing interests.

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Supplemental Material - 41587_2019_379_MOESM1_ESM.pdf

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Created:
August 22, 2023
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