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.
  
  

To run MetCell with blank substrate fucntion, the data folder 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.

• A superposition frame file for the blank sample generated by MetCell package: Please keep the original name generated by MetCell ('eim_peaks'). We provided demo file.
  
  

To generate the superposition frame file for the blank sample, the data folder should contain data files below:

• Raw data files (.d): The raw .d file of the blank sample.

• 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.
  
  

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)