Provided by: mcaller_1.0.3+git20210624.b415090-3_all
NAME
mCaller.py - find methylation in nanopore reads
DESCRIPTION
/usr/lib/python3/dist-packages/joblib/_multiprocessing_helpers.py:53: UserWarning: [Errno 13] Permission denied. joblib will operate in serial mode warnings.warn('%s. joblib will operate in serial mode' % (e,)) usage: mCaller [-h] (-p POSITIONS | -m MOTIF) -r REFERENCE -e TSV -f FASTQ [-t THREADS] [-b BASE] [-n NUM_VARIABLES] [--train] [--training_tsv TRAINING_TSV] [-d MODELFILE] [-s SKIP_THRESH] [-q QUAL_THRESH] [-c CLASSIFIER] [--plot_training] [-v] Classify bases as methylated or unmethylated optional arguments: -h, --help show this help message and exit -p POSITIONS, --positions POSITIONS file with a list of positions at which to classify bases (must be formatted as space- or tab-separated file with chromosome, position, strand, and label if training) -m MOTIF, --motif MOTIF classify every base of type --base in the motif specified instead (can be single one-mer) -r REFERENCE, --reference REFERENCE fasta file with reference aligned to -e TSV, --tsv TSV tsv file with nanopolish event alignment -f FASTQ, --fastq FASTQ fastq file with nanopore reads -t THREADS, --threads THREADS specify number of processes (default = 1) -b BASE, --base BASE bases to classify as methylated or unmethylated (A or C, default A) -n NUM_VARIABLES, --num_variables NUM_VARIABLES change the length of the context used to classify (default of 6 variables corresponds to 11-mer context (6*2-1)) --train train a new model (requires labels in positions file) --training_tsv TRAINING_TSV mCaller output file for training -d MODELFILE, --modelfile MODELFILE model file name -s SKIP_THRESH, --skip_thresh SKIP_THRESH number of skips to allow within an observation (default 0) -q QUAL_THRESH, --qual_thresh QUAL_THRESH quality threshold for reads (default none) -c CLASSIFIER, --classifier CLASSIFIER use alternative classifier: options = NN (default), RF, LR, or NBC (non-default may significantly increase runtime) --plot_training plot probabilities distributions for training positions (requires labels in positions file and --train) -v, --version print version