Single-cell-RNA-seq-of-the-CRISPR-engineered-endogenous-tauopathy-model

Output Details

scRNA-seq data analysis workflow Step1: bash cellranger_mkfastq.sh This will generate fastq files. Step2: bash cellranger_count_submission.sh This will call another bash file “cellranger_count.sh” and generate count tables Step3: bash run_scrublet_multi.sh This will call “scrublet_multi.py” and generate scrublet results. If seeing error refer to “scrublet_multi_conditional.py”. Step4: bash scRNA_seq.sh This will call “seurat_individual.R” and generate QC plots for each sample. Step5: Run Rscript hassan_merged_seurat.r -l expectedCells/ -s scrublet/ -k outdir/ -j hassan2022 -r refdir path_to_ref_directory This will generate Seurat results. Step6: Proceed with the trajectory and the fly phone DB analysis, using their respective code, on the integrated Seurat object. Step7: pySCENIC Step8: OmicsIntegrator
Tags
  • CRISPR
  • Drosophila
  • snRNA-seq (Single-nuclear RNA-seq)