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Immune profiling-based targeting of pathogenic T cells with ustekinumab in ANCA-associated glomerulonephritis

The manuscript is available at Nature Communications.

Instructions for single-cell analysis

Our single-cell analysis consists of two parts one for the exploratory cohort and another for the treatment (Ustekinumab) cohort. Both analysis follow the same general workflow of processing, clustering, annotation, and lastly more specific downstream analysis.

System requirements and installation

We ran the code in an Ubuntu 20.04 environment. The corresponding docker image can be obtained by running the following command:

docker pull imsbuke/dsnb:20211025_jh1.4.2

You can then run the docker image with the following command and replace /PATH_TO_DATA with the path to the data on your local machine:

docker run -it -v /PATH_TO_DATA:/data --user root --name ustekinumab-test imsbuke/dsnb:20211025_jh1.4.2 bash

To setup the single-cell analysis Python environment, please run the following commands:

conda update -n base conda
conda install -n base conda-libmamba-solver
conda config --set solver libmamba
export SKLEARN_ALLOW_DEPRECATED_SKLEARN_PACKAGE_INSTALL=True
conda env create -f envs/sc-env.yml
conda activate sc-env

To reproduce the figures you also need to install the Arial font. You can do this by running the following command:

apt-get update
apt-get upgrade -y
echo "ttf-mscorefonts-installer msttcorefonts/accepted-mscorefonts-eula select true" | sudo debconf-set-selections
echo "ttf-mscorefonts-installer msttcorefonts/accepted-mscorefonts-eula seen true" | sudo debconf-set-selections
apt-get install ttf-mscorefonts-installer -y
fc-cache -fv

For the R-parts of our analysis you need to install the following package:

setRepositories(ind=1:3)
install.packages("Signac")

Data preparation

You can find the Links to all raw and aligned single-cell data in Supplementary Table 10 of our manuscript. Please place the aligned data in separate folders in the data/single-cell/exploratory/alignment or data/single-cell/ustekinumab/alignmentdirectory.

For ease of use we provide the processed and annotated single-cell data for the both cohorts as MuData objects. This data is deposited at GEO under accession GSE253633 alongside the new single-cell data of this study. Please place the files in their respective folders in the data directory.

Analysis workflow

The analysis workflow for the single-cell data (CITEseq and scRNAseq) is detailed in the folder notebooks\single-cell. We further split the code for each cohort, namely the exploratory and the ustekinumab treatment cohort. The corresponding code is available in the folders notebooks\single-cell\exploratory_cohort and notebooks\single-cell\ustekinumab_cohort, respectively. Please use the notebooks in notebooks/single-cell/exploratory_cohort/00-preprocessing or notebooks/single-cell/ustekinumab_cohort/00-preprocessing for sample wise quality control and demultiplexing. Then you can proceed with the rest of the annotation workflow and downstream analysis.

Both folders also contain the code to reproduce the figures in the manuscript from the processed and annotated data objects, e.g., see notebooks\single-cell\exploratory_cohort\plot-main-figures.ipynb.

Instructions for Visium analysis

Dataset The aligned data and processed and annotated data objects are available at GSE250138. The raw data is available through SRA with bioproject PRJNA1052093.

For reproducibility, the docker image is available at Dockerhub and can be pulled using,

docker pull imsbuke/dsnb:20211025_jh1.4.2

The requirements regarding package versions is available in visium_requirements.txt and can be installed in docker container using,

pip install -r visium_requirements.txt

Data preparation

  1. Place the cellranger- and spaceranger (v2.0.1)-aligned data in a single folder where each subfolder is a Visium slide_ID (e.g. V1_D) and contains the alignment results for the slide_ID. Update the path to the aligned datasets in the first notebook.
  2. Place the TIF files corresponding to each spatial sample in the folder tif_processed.

The folders annotations_visium* contain expert-annotations of the Visium slides.

Analysis workflow

Guided code for required to reproduce the results is available in the folder notebooks. The second step of the processing is too big to push to GitHub, this can be downloaded from 02_cluster.ipynb

If you encounter any problem, please open an issue.