GSE119428
Recovery and analysis of transcriptome subsets from pooled single-cell RNA-seq libraries
Single-cell RNA sequencing (scRNA-seq) methods generate sparse gene expression profiles for thousands of single cells in a single experiment. The information in these profiles is sufficient to classify cell types by distinct expression patterns but the high complexity of scRNA-seq libraries prevents full characterization of transcriptomes from individual cells. To generate more focused gene expression information from scRNA-seq libraries, we developed a strategy to physically recover the DNA molecules comprising transcriptome subsets, enabling deeper interrogation of the isolated molecules by another round of DNA sequencing. We applied the method in both a cell-centric and gene-centric mode to isolate mRNA fragments from scRNA-seq libraries. Overall design: targeted resequencing and original untargeted datasets of various scRNA-Seq libraries from the 10x genomics and wafergen platform