An Example

Here we provide an example for how to run the workflow.

Metagenomic study: ERP124921 Metaproteomics: PXD005780

  1. Setting up the pipeline in your local machine, please follow the :doc:installation, then you should have a folder named as MetaPUF, in this folder, there are several subfolders, in the config folder, config.proteomics.yaml is the parameters that will be used in the pipeline, and the sample_info.csv file is the relationship table between the metaproteomics raw files and the metagenomics and/or metatranscriptomics assemblies, both of them are described in the :doc:inputs_outputs. In the resources folder, there are two protein reference fasta files, one contains the contaminat proteins and the other are the human reference proteomics, they are both described in our manuscript.

  2. Downloading the files from the PRIDE archive to the folder that you set in the config.proteomics.yaml file, the parameter folder for the RAW input files are ThermoFold, default value is input/Raw, which means you should first create this folder in the working directory if you are downloading files to your local machine. After downloading the files, you will need to create subfolders for each sample, for example sample S6.raw, create a subfolder named S6 under the path of input/Raw.

  3. Creating the relationship table, since we have downloaded the MS raw files locally, we don’t need the column Raw file URLs anymore, we can left this column as blank but will need to keep the header. The column Sample is the name of the metaproteomics sample, also the name of the subfolder that we just created for each sample. Raw file is the raw file name that we downloaded from the PRIDE archive, Sample Accession and Assembly are the metagenomics/metatranscriptomoics information from ENA/MGnify. Since some metaproteomics sample has multiple metagenomics/metatranscriptomics asseblies, we need to duplicate some columns.

  4. Please make sure the Proteomics analysis tools are all downloaded with the correct versions and paths. You will need to create subfolder workflow/bin under the working directory. And put the three tools there, with three seprate folders containing ThermoRawFileParser, SearchiGui and PeptideShaker.

  5. Now, you can use the command line to run the pipeline, please go to the Snakemake environment first with conda activate snakemake if you have set this environment. Then just run the command snakemake --cores 4. Because the whole pipeline runs quite long time, we suggest to use a job management tool to run the job remotely or run the job in background with screen command.

  6. You can view the generated output files in the folders that described in :doc: