Provided by: mcaller_1.0.3+git20210624.b415090-3_all bug

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