TY  - JOUR
N1  - The copyright of this article belongs to SPRINGER 
ID  - open3136
UR  - https://link.springer.com/article/10.1007/s00439-024-02678-x
A1  - Kumari, Pallawi
A1  - Kaur, Manmeet
A1  - Dindhoria, Kiran
A1  - Ashford, Bruce
A1  - Amarasinghe, Shanika L.
A1  - Thind, Amarinder Singh
Y1  - 2024///
N2  - Long-read single-cell transcriptomics (scRNA-Seq) is revolutionizing the way we profile heterogeneity in disease. Traditional short-read scRNA-Seq methods are limited in their ability to provide complete transcript coverage, resolve isoforms, and identify novel transcripts. The scRNA-Seq protocols developed for long-read sequencing platforms overcome these limitations by enabling the characterization of full-length transcripts. Long-read scRNA-Seq techniques initially suffered from comparatively poor accuracy compared to short read scRNA-Seq. However, with improvements in accuracy, accessibility, and cost efficiency, long-reads are gaining popularity in the field of scRNA-Seq. This review details the advances in long-read scRNA-Seq, with an emphasis on library preparation protocols and downstream bioinformatics analysis tools.
PB  - SPRINGER 
JF  - HUMAN GENETICS
TI  - Advances in long-read single-cell transcriptomics
ER  -