Missing data and technical variability in single-cell RNA-sequencing experiments
Harvard University · Dana-Farber Cancer Institute
Abstract
Until recently, high-throughput gene expression technology, such as RNA-Sequencing (RNA-seq) required hundreds of thousands of cells to produce reliable measurements. Recent technical advances permit genome-wide gene expression measurement at the single-cell level. Single-cell RNA-Seq (scRNA-seq) is the most widely used and numerous publications are based on data produced with this technology. However, RNA-seq and scRNA-seq data are markedly different. In particular, unlike RNA-seq, the majority of reported expression levels in scRNA-seq are zeros, which could be either biologically-driven, genes not expressing RNA at the time of measurement, or technically-driven, genes expressing RNA, but not at a sufficient…
Citation impact
- FWCI
- 21.86
- Percentile
- 100%
- References
- 77
Authors
4Topics & keywords
- RNA-Seq
- RNA
- Computational biology
- Gene expression
- Gene
- Biology
- Genetics
- Computer science