This repository contains the code used to perform the single-cell proteogenomic analysis of the human cell cycle. This study was based on immunofluorescence staining of ~200k cells for single-cell analysis of proteomic heterogeneity and ~1k cells for analysis of single-cell RNA variability. These analyses were integrated with other proteomic studies and databases to investigate the functional importance of transcript-regulated and non-transcript regulated variability.
The code is listed in order of execution, e.g. "1_", "2_" etc. The output of each script is used in the subsequent script. This workflow can also be run using snakemake (see below).
The logic for these analyses is contained in the SingleCellProteogenomics folder.
The input files are contained in the "input" folder. This folder is linked here for release v1.2 as a zip file, input.zip. Expand this folder within the base directory of this repository. If you are looking for the raw imaging proteomic dataset produced after filtering artifacts and such, that is located here.
The output files are added to a folder "output" during the analysis, and figures are added to a folder "figures."
An R-script used to analyze skewness and kurtosis (noted in the Methods of the manuscript) is contained in the other_scripts folder. The other_scripts/ProteinDisorder.py script utilizes IUPRED2A and a human UniProt database.
This workflow can be run using snakemake:
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Install Miniconda from https://docs.conda.io/en/latest/miniconda.html.
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Install snakemake using
conda install -c conda-forge snakemake-minimal. -
Within this directory, run
snakemake -j 1 --use-conda --snakefile workflow/Snakefile.
The single-cell RNA-Seq data is available at GEO SRA under project number GSE146773.
The cell cycle phase and FACS intensity information for these ~1,000 cells are contained in the input folder within three files, one per plate, starting with RNAData/180911_Fucci_single cell seq_ss2-18-*.csv. Raw FACS intensities, normalized FACS intensities, and calculated FUCCI pseudotime can also be found here.
The snakemake workflow used to analyze the scRNA-Seq dataset, including RNA velocity calculations and louvain unsupervised clustering, can be found in this repository: https://github.com/CellProfiling/FucciSingleCellSeqPipeline.
The loom file containing the results of RNA velocity analysis, including spliced and unspliced counts, can be found in the input folder under RNAData/a.loom, and the observation names used for each cell that match the "Well_Plate" identifiers can be found in RNAData/a.obs_names.csv.
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