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From fastq to preprocessed counttable (for in-house CELSeq2 method), with Kallisto | Bustools workflow.

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scRNA-seq preprocessing

From Kallisto | Bustools workflow counttable to preprocessed Seurat object.

FlowChart_scRNA-seqPreprocessing_sm

Installation

  1. Install Miniconda.

  2. Install Mamba

conda install mamba -n base -c conda-forge
  1. Download the newest release of scRNA-seq or clone the repository.
git clone https://github.com/Rebecza/scRNA-seq.git
  1. Create & activate environment.
cd scRNA-seq/envs
mamba env create -f kb_scrna_R_seurat3.yaml
conda activate kb_scrna_R_seurat3
  1. Install RStudio (optional)
mamba install -n kb_scrna_R_seurat3 r::rstudio

Note: RStudio should be started from within the conda environment.

  1. Running
  • RStudio: Open kb_seurat_pp.rmd -> Fill parameters -> Knit
  • Command-line: Run rmarkdown::render('kb_seurat_pp.rmd,....) from R console.

Running the alignment needed for scRNA-seq (and RNA Velocity)

The indexing and alignment for RNA Velocity can easily be performed with the scRNA-seq workflow of seq2science.

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From fastq to preprocessed counttable (for in-house CELSeq2 method), with Kallisto | Bustools workflow.

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