diffMONT

diffMONT is a python-based tool for predicting methylation-specific PCR (MSP) primers, based on Nanopore sequencing data. Given a merged bedmethyl file, diffMONT detects methylation-specific PCR primer regions, which can distinguish between two groups of samples (originally cancer patients vs. healthy controls).

Install:

We recommend to use linux and miniconda for the enviroment management

1. Download and install Conda.

2. Download the enviroment yml file diffMONT.yml

3. Create the Conda environment.

   conda env create -f diffMONT.yml

4. Activate the Conda environment. You will need to activate the Conda environment in each terminal in which you want to use diffMONT.

   conda activate diffMONT

Run:

Input for diffMONT is a bedmethyl file, sorted by genomic position, with an additional column containing the sample name. This file can be generated using the script preprocess.sh, which extracts the sample name from the file name. The most basic usage of diffMONT is via:

python diffMONT.py --bedmethylFile mergedMethylation.bed --controls ctr_1 ctr_2 --tumors tmr_1 tmr_2 --outfolder results/

The output of diffMONT is a list of predicted MSP regions, containing information for the forward and reverse primer. This list might contain overlapping MSP regions, which can be collapsed with the script groupPCRproducts.py.

Required parameters:

diffMONT has four required parameters.

• --bedmethylFile
  The merged bedmethyl file should follow the bedmethyl bed9+2 format, with an additional last column specifying the sample names.
• --controls
  The sample names of the control group, separated by space.
• --tumors
  The sample names of the non-control group, separated by space.
• outfolder Path to the where the results will be stored.

Optional parameters:

Optional parameters exist to adapt the requirements for the predicted MSP regions based on the user's requirements.

command	function
--maxMethControl	maximum average methylation allowed for the control sample
--minCpGs	minimum amount of differentially methylated cytosines in primer
--minPrimerLength	minimum length required for primers
--maxPrimerLength	maximum length required for primers
--minAmpliconLength	minimum length required for MSP regions
--maxAmpliconLength	maximum length required for MSP regions

Additionally, with the optional parameters --boxplotData and --primerData it is possible to continue the work from intermediate results. Further functionalities can be used by adding --annotation followed by an Ensembl annotation file, which will be screened for genes overlapping the predicted MSP regions (this will result in an additional output column). If the parameter --reference is set, followed by the reference genome, additional statistics like GC-content will be calculated and reported in additional output columns.