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Related Experiment Video

Updated: Sep 20, 2025

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples

Published on: June 8, 2020

nf-core/marsseq: systematic preprocessing pipeline for MARS-seq experiments.

Martin Proks¹, Jose Alejandro Romero Herrera², Jakub Sedzinski¹

¹Novo Nordisk Foundation Center for Stem Cell Medicine (reNEW), Department of Biomedical Sciences, University of Copenhagen, Copenhagen, 2200, Denmark.

Bioinformatics Advances

|May 29, 2025

Summary

This summary is machine-generated.

We standardized the Massively Parallel RNA Single cell Sequencing (MARS-seq) analysis pipeline for improved reproducibility and scalability. This updated pipeline enhances data interpretation and enables RNA velocity estimation for single-cell RNA sequencing studies.

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Area of Science:

Genomics
Bioinformatics
Molecular Biology

Background:

Single-cell RNA sequencing (scRNA-seq) is crucial for studying gene regulation.
Existing scRNA-seq protocols have limitations in standardization, data interpretation, and reproducibility.
Massively Parallel RNA Single cell Sequencing (MARS-seq2.0) offers reference data but has format limitations for analysis.

Purpose of the Study:

To standardize the MARS-seq analysis pipeline for improved reproducibility and data interpretation.
To adapt the MARS-seq pipeline for integration with the nf-core framework.
To incorporate RNA velocity estimation into the MARS-seq analysis workflow.

Main Methods:

Revised the original MARS-seq2.0 pipeline for implementation within the nf-core framework.
Integrated additional checkpoints for experimental metadata verification.
Developed a custom workflow for RNA velocity estimation.

Main Results:

Achieved simplified pipeline execution with increased transparency and scalability.
Enhanced the pipeline with improved metadata verification.
Successfully implemented a custom workflow for RNA velocity estimation.

Conclusions:

The updated MARS-seq pipeline offers a standardized and scalable approach for scRNA-seq data analysis.
The pipeline facilitates robust RNA velocity inference, advancing the study of gene regulation.
The nf-core integrated pipeline is freely available, promoting community-driven bioinformatics development.