DOKK / manpages / debian 12 / mcaller / mCaller.1.en
MCALLER.PY(1) User Commands MCALLER.PY(1)

mCaller.py - find methylation in nanopore reads

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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

show this help message and exit
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)
classify every base of type --base in the motif specified instead (can be single one-mer)
fasta file with reference aligned to
tsv file with nanopolish event alignment
fastq file with nanopore reads
specify number of processes (default = 1)
bases to classify as methylated or unmethylated (A or C, default A)
change the length of the context used to classify (default of 6 variables corresponds to 11-mer context (6*2-1))
train a new model (requires labels in positions file)
mCaller output file for training
model file name
number of skips to allow within an observation (default 0)
quality threshold for reads (default none)
use alternative classifier: options = NN (default), RF, LR, or NBC (non-default may significantly increase runtime)
plot probabilities distributions for training positions (requires labels in positions file and --train)
print version
June 2021 mCaller.py 1.0.3+git20210331.f7a616a