Hi everyone! As I was saying the in the #CE6SDEDAA channel, I’ve developed a bash/Slurm (for HPC) + R pipeline for single-cell RNA-seq preprocessing that takes .h5 files (like those generated by the nf-core scRNAseq pipeline) and outputs a Seurat R object (or Python equivalent) ready for downstream analysis, such as integration and clustering. The pipeline automates essential preprocessing steps, including ambient RNA removal, doublet detection, QC filtering, and normalization. While best practices are documented in the literature, many tutorials avoid these critical steps for simplicity, making the process challenging and time-consuming, especially for those new to the field. I haven’t come across a similar end-to-end solution, so I was wondering if porting this pipeline to Nextflow would be something useful for the community? @Phil Ewels suggested to ask here, and whether make sense to incorporate this in the main #CHN5BV5DW pipeline Thanks! Dom

Maybe also check #C077PUX8DBP. I do not know if it includes everything you need but as far as I know, it includes some ambient RNA removal, doublet detection, QC filtering as well as some downstream steps.

I forgot that one! https://nf-co.re/scdownstream/dev/

Yes, it seems very similar! Mine stops with the preprocessing. Maybe here there is missing a part about Hashtag handling. Maybe I can join that channel and see if I can contribute to that. Thanks

Perfect. Thanks all!

Hey @Domenico Somma, I'm the maintainer of #C077PUX8DBP - in case you still want to contribute, feel free to reach out. About hashtag handling, this will be tackled via #C067K2P6GUV - if you are motivated to contribute, feel free to reach out to that channel