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Snakemake analysis pipeline for FUCCI single-cell RNA-Seq data

Single-cell proteogenomic analysis

This repository contains the snakemake pipeline for analyzing the RNA sequencing data for ~1k single cells. The results of this single-cell RNA-Seq analysis provide a transcriptomic context to a proteomic analysis based on immunofluorescence staining of ~200k individual cells. For the code used to perform that single-cell proteogenomic analysis of the human cell cycle, please see the CellProfiling/SingleCellProteogenomics repository.

Single-cell sequencing files

The single-cell RNA-Seq data is available at GEO SRA under project number GSE146773.

This data is downloaded automatically in this pipeline.

Updating the Ensembl version

The genome and Ensembl versions are located at the top of the file workflow/config/FucciSingleCell.yaml. These can be updated, and the references will be downloaded automatically.

Usage

  1. Clone repository and initialize submodules: git clone --recurse-submodules https://github.com/CellProfiling/FucciSingleCellSeqPipeline.git && cd FucciSingleCellSeqPipeline/workflow
  2. Install conda: https://docs.conda.io/en/latest/miniconda.html
  3. Create and activate setup environment: conda env create -n fuccisetup -f envs/setup.yaml && conda activate fuccisetup
  4. Run the workflow: snakemake --use-conda --conda-frontend mamba --cores 24 --resources mem_mb=100000, where you can subsitute the max number of cores and max memory allocation. At least 54 GB of free memory should be available.

Usage on cluster

In place of installing conda, you may need to activate it as a module, such as by module load conda and then follow the instructions to initialize it.

Adapt config/cluster_config.yaml for your needs.

In place of the last step above, you can use the scheduler like this: snakemake -j 500 --cores 16 --cluster-config config/cluster_config.yaml --latency-wait 60 --keep-going --use-conda --conda-frontend mamba --cluster "sbatch -t {cluster.time} -N {cluster.nodes} --cpus-per-task {threads} -p {cluster.partition}"

Usage on protected access cluster

  1. Clone repository and initialize submodules on your local machine: git clone --recurse-submodules https://github.com/CellProfiling/FucciSingleCellSeqPipeline.git && cd FucciSingleCellSeqPipeline/workflow
  2. Install conda: https://docs.conda.io/en/latest/miniconda.html
  3. Create and activate setup environment: conda env create -n fuccisetup -f envs/setup.yaml && conda activate fuccisetup
  4. If running the pipeline on protected access computer, predownload files by running snakemake -j 16 ../results/setup.txt on a machine with internet access.
  5. Make a tarball of the project with cd ../.. && tar -cxvf FucciSingleCellSeqPipeline.zip FucciSingleCellSeqPipeline and transfer it to the protected access cluster.
  6. Load conda as a module on the protected access cluster, such as with module load conda, and follow the instructions to activate it.
  7. Create and activate setup environment: conda env create -n fuccisetup -f envs/setup.yaml && conda activate fuccisetup
  8. Adapt config/cluster_config.yaml for your needs.
  9. Use the scheduler from snakemake like this: snakemake -j 500 --cores 16 --cluster-config config/cluster_config.yaml --latency-wait 60 --keep-going --use-conda --conda-frontend mamba --cluster "sbatch -A {cluster.account} -t {cluster.time} -N {cluster.nodes} --cpus-per-task {threads} -p {cluster.partition}"

Citation

Mahdessian, D.*; Cesnik, A. J.*; Gnann, C.; Danielsson, F.; Stenström, L.; Arif, M.; Zhang, C.; Le, T.; Johansson, F.; Shutten, R.; Bäckström, A.; Axelsson, U.; Thul, P.; Cho, N. H.; Carja, O.; Uhlén, M.; Mardinoglu, A.; Stadler, C.; Lindskog, C.; Ayoglu, B.; Leonetti, M. D.; Pontén, F.; Sullivan, D. P.; Lundberg, E. “Spatiotemporal dissection of the cell cycle with single cell proteogenomics.” Nature, 2021, 590, 649–654. *Contributed equally. https://www.nature.com/articles/s41586-021-03232-9