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MapMetSC

DOI DOI Suggestions Welcome

This repository is currently under development.

This repository provides scripts to reproduce figures published in Lazic et al (in preparation). In brief, we spatially and temporally mapped primary and metastatic neuroblastoma by multi-modal high-plex imaging in combination with scRNA-seq datasets. The data analysis worflow in Lazic et al. is split into two parts:

  • MapMetIP: python based image-processing pipeline
  • MapMetSC: R based single-cell analysis worfklow

Data

Single-cell data can either be obtained by downloading raw images from Zenodo (MapMetIP_FullDataset.zip) and processing these using MapMetIP or by directly downloading MapMetIP-processed data from Zenodo (MapMetIP_ProcessedDataset.zip). For download, replace path/to/extract/directory with the absolute path to the directory, where the data should be stored.

wget -P <path/to/extract/directory> https://zenodo.org/records/13220635/files/MapMetIP_ProcessedDataset.zip
unzip <path/to/extract/directory>/MapMetIP_ProcessedDataset.zip -d <path/to/extract/directory>
rm <path/to/extract/directory>/MapMetIP_ProcessedDataset.zip

Alternatively, the R object containing already MapMetSC-processed single cell data with all annotations (cell types, metaclusters, etc.) can be downloaded from Zenodo (spe_final.rds).

Usage

Clone the repository via

git clone https://github.com/TaschnerMandlGroup/MapMetSC.git

For reproducibility, we provide a docker image. Pull the docker image using:

docker pull lazdaria/mapmetsc:v1.0

and run a container from that image:

docker run -p 8787:8787 -e PASSWORD=mapmetsc -v <path/to/MapMetSC>:/home/rstudio/MapMetSC -v <path/to/extracted/singlecelldata>:/mnt/data lazdaria/mapmetsc:v1.0

An RStudio server session can then be accessed via your browser at localhost:8787 with the username: rstudio and password: mapmetsc. Due to a bug fix for the testInteractions function in later versions of imcRtools, we provide another docker image (lazdaria/mapmetsc_spatial:v1.0) for spatial analysis.

To reproduce results from Lazic et al., proceed with the provided RMD files. Alternatively, already rendered html files are provided to demonstrate each step of the pipeline.

Cell-cell communication (CCC) analysis

To reproduce CCC analysis results on public single-cell RNA-sequencing data from Fetahu et al., as described in Lazic et al., we provide a separate docker image. Pull the image from docker hub via:

docker image pull swernig/mapmet_paper:v1.2

Afterwards, proceed with RMD files in the folder CCC_analysis.

Contributors

Funding

This work was funded by the Austrian Science Fund (FWF#I4162 and FWF#35841), the Vienna Science and Technology Fund (WWTF; LS18-111), the Swiss Government Excellence Scholarship and the St. Anna Kinderkrebsforschung e.V.