Specific splice junction detection in single cells with SICILIAN

Authors

Roozbeh Dehghannasiri, Stanford University
Julia E. Olivieri, Stanford UniversityFollow
Ana Damljanovic, Seven Bridges Genomics Inc.
Julia Salzman, Stanford University

Department

Computer Science

Document Type

Article

Publication Title

Genome Biology

ISSN

1474-7596

Volume

22

Issue

1

DOI

10.1186/s13059-021-02434-8

Publication Date

12-1-2021

Abstract

Precise splice junction calls are currently unavailable in scRNA-seq pipelines such as the 10x Chromium platform but are critical for understanding single-cell biology. Here, we introduce SICILIAN, a new method that assigns statistical confidence to splice junctions from a spliced aligner to improve precision. SICILIAN is a general method that can be applied to bulk or single-cell data, but has particular utility for single-cell analysis due to that data’s unique challenges and opportunities for discovery. SICILIAN’s precise splice detection achieves high accuracy on simulated data, improves concordance between matched single-cell and bulk datasets, and increases agreement between biological replicates. SICILIAN detects unannotated splicing in single cells, enabling the discovery of novel splicing regulation through single-cell analysis workflows.

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Recommended Citation

Dehghannasiri, R., Olivieri, J. E., Damljanovic, A., & Salzman, J. (2021). Specific splice junction detection in single cells with SICILIAN. Genome Biology, 22(1), DOI: 10.1186/s13059-021-02434-8
https://scholarlycommons.pacific.edu/soecs-facarticles/309