Single-cell combinatorial indexing RNA sequencing (sci-RNA-seq) is a powerful method for
recovering gene expression data from an exponentially scalable number of individual cells …

Large-scale sequencing of RNA from individual cells can reveal patterns of gene, isoform
and allelic expression across cell types and states. However, current short-read single-cell …

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 …

Emerging methods for the accurate quantification of gene expression in individual cells hold
promise for revealing the extent, function and origins of cell-to-cell variability. Different high …

Background: Single cell RNA sequencing (scRNA-seq) has rapidly gained popularity for
profiling transcriptomes of hundreds to thousands of single cells. This technology has led to …

Current approaches to single-cell transcriptomic analysis are computationally intensive and
require assay-specific modeling, which limits their scope and generality. We propose a …

Single-cell RNA sequencing (RNA-seq) is a powerful tool to reveal cellular heterogeneity,
discover new cell types and characterize tumor microevolution. However, losses in cDNA …

In the last few years single-cell RNA sequencing (scRNA-seq) has enabled the investigation
of cellular heterogeneity at the transcriptional level, the characterization of rare cell types as …

Single-cell RNA sequencing (scRNA-seq) is a popular and powerful technology that allows
you to profile the whole transcriptome of a large number of individual cells. However, the …

High-throughput mRNA sequencing (RNA-Seq) promises simultaneous transcript discovery
and abundance estimation,,. However, this would require algorithms that are not restricted …