In single-cell RNA sequencing (scRNA-seq) studies, only a small fraction of the transcripts present in each cell are sequenced. This leads to unreliable quantification of genes with low or moderate expression, which hinders downstream analysis. To address this challenge, University of Pennsylvania researchers developed SAVER (single-cell analysis via expression recovery), an expression recovery method for unique molecule index (UMI)-based scRNA-seq data that borrows information across genes and cells to provide accurate expression estimates for all genes.
RNA FISH validation of SAVER results on Drop-seq data
a, Overview of SAVER procedure. b, Comparison of the Gini coefficient for each gene between FISH and Drop-seq (left) and between FISH and SAVER recovered values (right) for n = 15 genes. c, Kernel density estimates of cross-cell expression distributions of LMNA (top) and CCNA2 (bottom). d, Scatter plots of expression levels for BABAM1 and LMNA. Pearson correlations were calculated across n = 17,095 cells for FISH and n = 8,498 cells for Drop-seq and SAVER.
Availability – The R package for SAVER is available at: https://github.com/mohuangx/SAVER
Huang M, Wang J, Torre E, Dueck H, Shaffer S, Bonasio R, Murray JI, Raj A, Li M, Zhang NR. (2018) SAVER: gene expression recovery for single-cell RNA sequencing. Nat Methods [Epub ahead of print]. [abstract]