Characterizing the replicability of cell types defined by single cell RNA-sequencing data using MetaNeighbor.

ABSTRACT: Single-cell RNA-sequencing (scRNA-seq) technology provides a new avenue to discover and characterize cell types; however, the experiment-specific technical biases and analytic variability inherent to current pipelines may undermine its replicability. Meta-analysis is further hampered by the use of ad hoc naming conventions. Here we demonstrate our replication framework, MetaNeighbor, that quantifies the degree to which cell types replicate across datasets, and enables rapid identification of clusters with high similarity. We first measure the replicability of neuronal identity, comparing results across eight technically and biologically diverse datasets to define best practices for more complex assessments. We then apply this to novel interneuron subtypes, finding that 24/45 subtypes have

SUBMITTER: Crow M 

PROVIDER: S-EPMC5830442 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature