期刊
NATURE METHODS
卷 14, 期 4, 页码 381-+出版社
NATURE PORTFOLIO
DOI: 10.1038/nmeth.4220
关键词
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资金
- Cancer Research UK [C45041/A14953]
- European Research Council [677501-ZF_Blood]
- Wellcome Trust
- MRC
- ERC grant ThSWITCH [260507]
- Lister Institute Research Prize
- Biotechnology and Biological Sciences Research Council [BBS/E/T/000PR9819] Funding Source: researchfish
- Cancer Research UK [14953] Funding Source: researchfish
- Medical Research Council [MC_PC_12009] Funding Source: researchfish
- BBSRC [BBS/E/T/000PR9819] Funding Source: UKRI
Single-cell RNA sequencing (scRNA-seq) has become an established and powerful method to investigate transcriptomic cell-to-cell variation, thereby revealing new cell types and providing insights into developmental processes and transcriptional stochasticity. A key question is how the variety of available protocols compare in terms of their ability to detect and accurately quantify gene expression. Here, we assessed the protocol sensitivity and accuracy of many published data sets, on the basis of spike-in standards and uniform data processing. For our workflow, we developed a flexible tool for counting the number of unique molecular identifiers (https://github.com/vals/umis/). We compared 15 protocols computationally and 4 protocols experimentally for batch-matched cell populations, in addition to investigating the effects of spike-in molecular degradation. Our analysis provides an integrated framework for comparing scRNA-seq protocols.
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