Assessing the reliability of spike-in normalization for analyses of single-cell RNA sequencing data.

ABSTRACT: By profiling 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-specific biases in capture efficiency and library generation. One strategy for removing these biases is to add a constant amount of spike-in 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 different 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 al

SUBMITTER: Lun ATL 

PROVIDER: S-EPMC5668938 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature