zhulab/metcell-r repository overview

⁠MetCell

⁠Introduction

MetCell is an R package for end-to-end data processing for single-cell metabolomics. Now MetCell supports data processing from ion mobility-resolved mass cytometry (specifically timsTOF pro) with cell superposition and bottom-up assembly peak detection algorithm.

The docker image zhulab/metcell-r⁠ contains entire environment for running MetCell. For convenience and taking fully use of MetCell, users can pull it and run MetCell just as following.

⁠What is metcell-r

metcell-r is a Docker environment to processing ion mobility-resolved mass cytometry data with MetCell R package. It is based on the r-base⁠ docker.

⁠Pulling image

Users can pull the metcell-r image with the following script

docker pull zhulab/metcell-r

⁠Data preparation

The data folder to run MetCell should contain data files below:

• Raw data files (.d): Only one data file should be put in the file folder. And the file corresponding to the demo R script below could be download at the deposit⁠. (If you use this demo file, remember to UNZIP the data into .d format before you run MetCell)

• R script: we provided demo code⁠. The R script must be named as "run.R". Parameters were described in the script.

• Time segment table: A .csv table recorded the time segment of raw file to be processed. The table must be named as "time_limit_table.csv". we provided demo file⁠. The colnames of the table must not be modified. The contain of 'data_file' column should be the same as your raw data file name. And start_time and end_time defined the time segment you want to process in the raw data, and the unit is second.
  
  

⁠Run data processing work with metcell-r image

• go to your data folder (e.g., data)

 cd data

• run docker using following code (User should be permitted to run docker service)

# MUST keep the code exactly as it is!
docker run -it --rm -v "$PWD":/data -u $(id -u ${USER}):$(id -g ${USER}) zhulab/metcell-r Rscript run.R

• wait till data processing work done

• docker run argument explanation:

  -v "$PWD":/home/${USER}: mapping current directory as home directory in docker container

  -u $(id -u ${USER}):$(id -g ${USER}): using current user to run the container

  Rscript ~/run.R: run run.R in container home directory with Rscript command

⁠The result

After the data processing work done, a folder name 'results' would be generated in the root folder. And the main results are listed following:

• "01_feature_table.csv": all detected peaks and their quantification in all individual cells;

• "02_isotope_annotation_table.csv": isotope annotation results for singly charged peaks and their quantification in all individual cells;

• "03_metabolite_annotation_table.csv": putative metabolite annotation results for singly charged peaks through MS1 and CCS match with the library and their quantification in all individual cells.

⁠License

This work is licensed under the Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)