New pipeline: nf-core/eisca

[huihai828]

Pipeline title/name

eisca

Keywords

single-cell, scRNA-seq, 10x, Smart-seq2, scvi-tools

What is it about?

EISCA is a bioinformatics pipeline that performs analysis of single-cell RNA-seq data. It was developed as a generalized, flexible, and scalable workflow for scRNA-seq analysis. The pipeline is primarily designed for droplet-based (10x) and plate-based (Smart-seq2) data. The pipeline consists of three analysis phases. The primary phase includes raw data QC, mapping and quantification, and converting count matrix into Anndata. The secondary phase focuses on single-cell QC, cell filtering, clustering analysis with integration. The tertiary phase involves downstream analyses, such as cell type annotation, differential expression analysis, cellular interaction analysis. Users can run the pipeline end-to-end or execute each analysis phase independently.

Please provide a schematic diagram of the proposed pipeline

I confirm my proposed pipeline will follow nf-core guidelines. Most importantly, my pipeline will:

• be built with Nextflow.
• pass nf-core lint tests and use standardized parameters.
• be community-owned and developed within the nf-core organization.
• open source under the MIT license with proper credits and acknowledgments.
• have a descriptive, all lowercase, and without punctuation name.
• use the nf-core pipeline template and predominantly use official nf-core modules.
• focus on a specific data/analysis type with appropriate scope.
• have properly maintained documentation.
• be bundled using versioned Docker/Singularity containers.

Why do we need a new pipeline?

This is full-spectrum analysis pipeline for single-cell data from preprocessing the raw data to filtering, clustering and downstream analyses. This pipeline support multiple starting points, allowing users to begin from raw FASTQ files or processed single-cell Anndata for different analysis phases. Users can tweak parameters and re-run specific analysis to gain better insights. This flexibility enables users to quickly perform preliminary analyses and obtain an out-of-the-box analysis report showing QC metrics and plots. This facilitates rapid assessment of data quality, and supports a smooth transition to more complex, objective-specific downstream analyses. Additionally, the pipeline integrates scvi-tools for data integration, annotation, and differential expression analysis by applying pretrained models or training custom models.

Who would be interested?

Researchers and bioinformaticians working with single-cell RNA-seq data, especially those needing a flexible, scalable, and end-to-end analysis workflow would be most interested in EISCA. This includes labs analyzing 10x or Smart-seq2 data, computational biologists performing QC, clustering, or integration, and teams looking for reproducible pipelines with scvi-tools support.

What has been done so far

The pipeline has been under active development for about one year and has reached version 2.5. It has been tested extensively within our institute, where we have validated its performance across multiple datasets and refined its features based on real analysis needs.

URL to existing work (if applicable)

https://github.com/EarlhamInst/eisca

Are there any similar existing nf-core pipelines?

scrnaseq, scdownstream

[nf-core-bot]

Approval status: 🕐 Pending

Required approvals: Either 2 core team members OR 1 core team member + 1 maintainer

Review Status	Team members
❌ Rejected	@jfy133, @nictru
🕐 Pending (Core)	@ewels, @maxulysse, @mribeirodantas, @mashehu, @JoseEspinosa, @mirpedrol, @FriederikeHanssen, @kenibrewer, @edmundmiller, @sateeshperi, @FranBonath, @christopher-hakkaart, @nvnieuwk
🕐 Pending (Maintainer)	@pontus, @maxulysse, @lpantano, @pinin4fjords, @mashehu, @JoseEspinosa, @mirpedrol, @GallVp, @FloWuenne, @matthdsm, @FriederikeHanssen, @adamrtalbot, @mahesh-panchal, @jfy133, @atrigila, @prototaxites, @ramprasadn, @edmundmiller, @luisas, @SPPearce, @vagkaratzas, @sateeshperi, @jonasscheid, @famosab, @itrujnara, @LouisLeNezet, @Joon-Klaps, @jasmezz, @Felix-Kummer, @sofstam, @nvnieuwk

[nf-core-bot]

Approval status: 🕐 Pending

Required approvals: Either 2 core team members OR 1 core team member + 1 maintainer

Review Status	Team members
🕐 Pending (Core)	@ewels, @maxulysse, @mribeirodantas, @mashehu, @JoseEspinosa, @mirpedrol, @FriederikeHanssen, @kenibrewer, @jfy133, @edmundmiller, @sateeshperi, @FranBonath, @christopher-hakkaart, @nvnieuwk
🕐 Pending (Maintainer)	@pontus, @maxulysse, @lpantano, @pinin4fjords, @mashehu, @JoseEspinosa, @mirpedrol, @GallVp, @FloWuenne, @matthdsm, @FriederikeHanssen, @adamrtalbot, @mahesh-panchal, @jfy133, @atrigila, @prototaxites, @ramprasadn, @edmundmiller, @luisas, @SPPearce, @vagkaratzas, @sateeshperi, @jonasscheid, @famosab, @nictru, @itrujnara, @LouisLeNezet, @Joon-Klaps, @jasmezz, @Felix-Kummer, @sofstam, @nvnieuwk

[mashehu]

what makes it different from scrnaseq and scdownstream?

[huihai828]

what makes it different from scrnaseq and scdownstream?

I have reviewed the scdownstream pipeline, and it overlaps substantially with our pipeline EISCA. In fact, scdownstream includes additional modules, particularly for ambient RNA removal and doublet detection. I agree that EISCA is somehow redundant for the nf-core. Thanks!

[JoseEspinosa]

Thanks @huihai828 for the feedback.
If you think that some of the features implemented in eisca would strengthen scrnaseq, we’d be delighted to work together on bringing them into the pipeline.

[huihai828]

@JoseEspinosa, thanks for suggestion! Compared to scdownstream, eisca includes additional downstream analyses, such as differential expression analysis (DEA), cell–cell communication analysis, and annotation and DEA using scvi-tools. I would like to contribute to the nf-core.

[jfy133]

Given the discussion above implying a large overlap, so I will say

/reject

this proposal as it stands, but not because of the because I see lots of potential to expand existing pipelines (nf-core/scdownstream, nf-core/differentialabundance). I believe both pipelines are looking for additional developer team members, so it would be great to strengthen thsee teams.

Would it thus be otherwise OK to close this proposal, filed under 'merge with exsisting'?

[nictru]

Hey, sorry for missing this discussion. I am the main developer of scdownstream and helping with scrnaseq. As I am currently doing an internship, I'm a bit stretched thin concerning following new pipeline proposals and scdownstream development.

The idea of scdownstream was to merge different efforts of single-cell transcriptomics pipelines and take the best of everyone. When looking at the eisca metro map I see that most of the steps listed are available in scrnaseq and scdownstream.
However, the scvi-tools differential expression is missing in scdownstream (this is not something that should be done in differentialabundance, as it is single-cell specific). I could imagine adding it to scdownstream, and if you want to contribute, you're more than welcome.

So I agree with @jfy133 to close as 'merge with existing'

/reject

[huihai828]

Thank you @jfy133 and @nictru for the review. I totally agree that scrnaseq and scdownstream cover most of the functionality for single-cell RNA-seq analysis, and that we should avoid redundancy for nf-core. I may consider raising an issue for scVI-based DEA in scdownstream. I will close this proposal.