Computational approach to evaluate scRNA-seq data quality and gene body coverage with SkewC
Summary: SkewC is a single-cell RNA sequencing (scRNA-seq) data quality evaluation tool. The approach is based on determining gene body coverage, and its skewness, as a quality metric for each individual cell. SkewC distinguishes between two types of single cells: typical cells with prototypical gen...
Main Authors: | Imad Abugessaisa, Akira Hasegawa, Shintaro Katayama, Juha Kere, Takeya Kasukawa |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2023-03-01
|
Series: | STAR Protocols |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2666166722009170 |
Similar Items
-
Protocols for single-cell RNA-seq and spatial gene expression integration and interactive visualization
by: Surbhi Sona, et al.
Published: (2023-03-01) -
scRNA‐seq data analysis method to improve analysis performance
by: Junru Lu, et al.
Published: (2023-05-01) -
scRNASequest: an ecosystem of scRNA-seq analysis, visualization, and publishing
by: Kejie Li, et al.
Published: (2023-05-01) -
Protocol for base resolution mapping of ac4C using RedaC:T-seq
by: David Sturgill, et al.
Published: (2022-12-01) -
Computational workflow for investigating highly variable genes in single-cell RNA-seq across multiple time points and cell types
by: Jantarika Kumar Arora, et al.
Published: (2023-09-01)