Contents
What is dropout in single cell RNA-seq?
One important characteristic of scRNA-seq data that feeds into all these challenges is a phenomenon called “dropout”, where a gene is observed at a low or moderate expression level in one cell but is not detected in another cell of the same cell type16.
How many cells are in a 10x chip?
80,000 cells
10x Genomics Single Cell Features Samples are barcoded individually for a multiplexed sequencing reaction. 10x Chromium instrument capable of capturing 100 to 10,000 cells per sample; up to 80,000 cells per chip in ~7 minutes.
What does flow cytometry tell you?
Flow cytometry is a laboratory method used to detect, identify, and count specific cells. This method can also identify particular components within cells. This information is based on physical characteristics and/or markers called antigens on the cell surface or within cells that are unique to that cell type.
Are there doublets in single cell RNA sequencing?
Single-cell RNA sequencing (scRNA-seq) data are commonly affected by technical artifacts known as “doublets,” which limit cell throughput and lead to spurious biological conclusions. Here, we present a computational doublet detection tool-DoubletFinder-that identifies doublets using only gene expression data.
What is the doublet rate in 10x sequencing?
“Doublet” is commonly used to describe a droplet in droplet-based sequencing that has captured atleast 2 cells. 10x states their doublet rate to be 0.8% per 1000 cells: There is a tradeoff between targeted cell capture and doublet rate and lab protocols are usually optimized for a certain expected doublet rate.
Are there any computational methods to detect doublets?
Computational methods have been developed to detect doublets in scRNA-seq data; however, the scRNA-seq field lacks a comprehensive benchmarking of these methods, making it difficult for researchers to choose an appropriate method for specific analyses.
How is doubletfinder used to identify differentially expressed genes?
We first use scRNA-seq datasets where the identity of doublets is known to show that DoubletFinder identifies doublets formed from transcriptionally distinct cells. When these doublets are removed, the identification of differentially expressed genes is enhanced.