MicSearch

A fully automated workflow for identification of microcins using HMMER.

MicSearch (Cinful v2) is developed by the Wilke lab at the Department of Integrative Biology in collaboration with the Davies lab at the Department of Molecular Biosciences, both at The University of Texas at Austin.

Installation

Setting up conda environment:

conda create --name <environment_name> python=3.8
conda activate <environment_name>

Installing dependencies:

conda install mamba -c conda-forge
mamba install biopython=1.79 blast=2.14 hmmer=3.3 mafft=7.508 numpy=1.24 pandas=1.5 snakemake=7.18 -c conda-forge -c bioconda

Downloading repository:

git clone https://github.com/AaronFeller/MicSearch.git

Running MicSearch:

Testing your install:

If downloaded properly, running python MicSearch.py -h should give you a list of instructions.

Basic run:

cd MicSearch
conda activate <environment_name>
python MicSearch.py -d resources/test_genome -o test_run -t <number_of_threads>

The precomputed results from this test are contained in the test_genome folder for your comparison.

File naming required

This pipeline will only identify files that end in the extension '.fna'. If you are working with another extension, the simplest fix is to rename these files and add the .fna extension.

Deleting temp files:

You are able to manually delete temp files contained in the temp folder inside of your output directory.

Additionally, including the argument -x will remove the temp folder at runtime.

After analysis has completed without the -x command and you would like to remove the temp files, you can rerun the same command with -x and they will be removed.

python MicSearch.py -d resources/test_genome -o test_run -t <number_of_threads> -x

Contributing

MicSearch currently exists as a wrapper to a series of snakemake rules, so adding functionality to it is as simple as adding additional rules. If there are any additions that you feel are needed, feel free to raise an issue.