Quick binning and frame-shift correction of long read metagenomic assemblies using DIAMOND+MEGAN pipeline with dynamically created reference DB
QuickBinDM is a bioinformatics pipeline designed to efficiently perform metagenomic binning of contigs generated from nanopore sequencing. The pipeline integrates DIAMOND, MEGAN, and Skani to create a dynamic DIAMOND database, which significantly speeds up the binning process.
Clone the repository to your local machine:
git clone https://github.com/lucast122/QuickBinDM.git
- Python 3.x
- DIAMOND
- MEGAN
- Skani
Please make sure to install the dependencies before running the pipeline.
Navigate to the directory containing quickbindm.py
and execute the following command:
python quickbindm.py -i <input_contigs> -r <reference_seqs> -o <output_folder> [options]
-i, --input_contigs
: The path to the input contigs after assembly and possibly assembly correction. Should be a FASTA or FASTQ file.-r, --reference_seqs
: The path to the reference sequences for creating the database. Should be a FASTA or FASTQ file.-o, --output_folder
: The path to the output folder that will contain the results.
-t, --threads
: The number of threads to use. Default is 1.-a, --ani
: The ANI (Average Nucleotide Identity) cutoff. Default is 95.-q, --querycoverage
: The minimum query coverage for ANI calculation. Default is 80.-c, --refcoverage
: The minimum reference coverage for ANI calculation. Default is 80.
python quickbindm.py -i input_contigs.fasta -r reference_seqs.fasta -o output/ -t 4 -a 95 -q 80 -c 80