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Related Experiment Video

Updated: May 28, 2025

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data

Published on: June 24, 2021

ELLIPSIS: robust quantification of splicing in scRNA-seq.

Marie Van Hecke^1,2,3, Niko Beerenwinkel^4,5, Thibault Lootens^3,6,7

¹IDLab, Department of Information Technology, Ghent University-IMEC, 9052 Ghent, Belgium.

Bioinformatics (Oxford, England)

|February 12, 2025

Summary

This summary is machine-generated.

A new tool, ELLIPSIS, robustly quantifies alternative splicing in single-cell RNA sequencing (scRNA-seq) data. It identifies differential splicing in cancer cells, revealing genes involved in cell migration and guidance.

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Area of Science:

Genomics
Computational Biology
Molecular Biology

Background:

Alternative splicing is a crucial, cell-type-specific regulatory process.
Quantifying splicing in single-cell RNA sequencing (scRNA-seq) is difficult due to low and uneven data coverage.

Purpose of the Study:

To develop a robust method for quantifying alternative splicing in scRNA-seq data.
To enable the detection of differential splicing, including novel splicing events, particularly in cancer cells.

Main Methods:

Developed ELLIPSIS, a computational tool for splicing quantification.
Leveraged local read coverage, flow conservation, and intra-cell type similarity.
Applied ELLIPSIS to simulated and glioblastoma scRNA-seq data.

Main Results:

ELLIPSIS accurately estimates Percent Spliced In values from simulated data.
The tool reliably detects differential splicing between cell types.
Identified differentially spliced genes in glioblastoma, linked to cell migration and neuronal guidance.

Conclusions:

ELLIPSIS provides a robust solution for splicing analysis in scRNA-seq.
The identified genes offer insights into glioblastoma progression and cell behavior.