BinLorry: a flexible tool for binning and filtering sequencing reads
BinLorry is a flexible tool for binning and filtering sequencing reads into distinct files. Reads can be binned and filtered by any attributes encoded in their headers, documented in a CSV file or by length.
Simply install with pip:
pip3 install binlorry
Install from repository
Clone the repository:
git clone https://github.com/rambaut/binlorry.git
pip3 install ./binlorry
Run without installation
BinLorry can also be run directly from the repository clone, without installation:
git clone https://github.com/rambaut/binlorry.git python binlorry/binlorry-runner.py -h
However, ensure that the
pandas package is installed before use.
Quick Usage Examples
binlorry -i reads/ -o barcode --bin-by barcode --filter-by barcode BC01 BC02 -n 550 -x 750
This would read all FASTQ or FASTA files in the directory
reads, bin by the header field
barcode, but only if this is
BC02 and if the length is between 550 and 750 nucleotides.
It would use the file name prefix
barcode resulting in the files:
binlorry -i my_file.fastq -t my_file.csv --out-report -o filtered --filter-by reference Type_1 -n 550 -x 750
The above example will take in reads from
my_file.fastq and a csv report
my_file.csv. Assuming that
my_file.csv has at least the structure shown below, and that the read names in the csv match those in the input read file, BinLorry will filter reads and output only those with Type_1 reference between 550 and 750 bases in length.
binlorry -i path/to/my_fastq_dir -t path/to/my_csv_dir \ --out-report -o path/to/binned/barcode \ --filter-by barcode BC01 --bin-by barcode -n 1000 -x 2000
Assuming you have reports in the csv dir corresponding to the read files in the fastq dir, binlorry will recursively search both directories, matching the csv and fastq files based on filename stem. This command will then filter reads only containing BC01 and output a csv report corresponding to the reads presented in the output fastq file.
Command line interface
usage: binlorry -i INPUT [-t CSV_FILE] -o OUTPUT [-v VERBOSITY] [--bin-by FIELD [FIELD ...]] [--filter-by FILTER [FILTER ...]] [-n MIN] [-x MAX] [-h] [--version] Main options: -i INPUT, --input INPUT FASTA/FASTQ of input reads or a directory which will be recursively searched for FASTQ files (required) -t INPUT_CSV, --index-table INPUT_CSV A CSV file with metadata fields for reads (otherwise these are assumed to be in the read headers). This can also include a file and line number to improve performance. Assumes read name is first column of the csv.' -o OUTPUT, --output OUTPUT Output filename (or filename prefix) -r REPORT, --out-report REPORT Output a subsetted csv report along with the fastq. (Default: False) Only implemented for use in conjunction with -t option. -f FORCE_OUTFILES, --force-output FORCE_OUTFILES Output binned/ filtered files even if empty. (default: False) Usage: only a single binning factor with a corresponding filter factor. -v VERBOSITY, --verbosity VERBOSITY Level of progress information: 0 = none, 1 = some, 2 = lots, 3 = full - output will go to stdout if reads are saved to a file and stderr if reads are printed to stdout (default: 1) Binning/Filtering options: --bin-by FIELD [FIELD ...] Specify header field(s) to bin the reads by. For multiple fields these will be nested in order specified. --filter-by FILTER [FILTER ...] Specify header field and accepted values to filter the reads by. Multiple filter-by options can be specified. -n MIN, --min-length MIN Filter the reads by their length, specifying the minimum length. -x MAX, --max-length MAX Filter the reads by their length, specifying the maximum length. Help: -h, --help Show this help message and exit --version Show program's version number and exit
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