Snakemake pipeline for basic processing of metagenomic data from the lab. It accepts raw fastq files of metagenomic data, quality filters it, removes reads that map to the host genome, then builds assemblies of each sample and generates a sourmash profile. The current version also generates a taxonomic profile of each sample using MetaPhlAn3. Modules that are currently underdevelopment will handle automated binning procedures, as well as strain-level profiling.
First, clone this github repository:
$ git clone https://github.com/CUMoellerLab/sn-mg-pipeline.git
cd sn-mg-pipeline
We recommend installing and using mamba:
$ conda install -c conda-forge mamba
Then install the snakemake version for this workflow using mamba:
$ mamba env create -n snakemake -f resources/env/snakemake.yaml
$ conda activate snakemake
Now you can update three files that are located in the ./resources/config directory.
The first two files are samples.txt and units.txt. The samples.txt file is your basic metadata file, with each row representing a sample in your dataset and each column containing the corresponding information about that sample. The first column should named "Sample" and should contain the name for each sample. Any addition columns are not used at this step.
The units.txt file should have only 4 columns, and each row should correspond to a sample found in the samples.txt file. The first column, "Sample", should be all or a subset of the "Sample" column in the samples.txt file. The second column, "Unit", should denote which analysis block each sample belongs to. In our case, we use sequencing run/lane, but you may use other information based on your experimental design. The third and fourth columns (named "R1" and "R2", respectively) should include the full file paths to the forward and reverse fastq files for that sample.
The last file to update is the the config.yaml file. This is where you can select the parameters for each step in the analysis pipeline. Refer to the documentation for each tool individually for more information. Also, be sure to change the NCBI GenBank Accession number to your host of interest.
NOTE: You can select which metagenomic assembler you want to use under the the "assemblers:" header. The current options are metaSPAdes and MEGAHIT Simply delete the assembler you don't want to use. Otherwise both will run.
After you have updated the files described above, you can start the pipeline. First run:
conda install -n base -c conda-forge mamba
Then begin the run using:
snakemake --cores 8 --use-conda
The first time you run this, it may take longer to set up your conda environment. Be sure to select the appropriate number of cores for your analysis.