nanomotif 0.1.19

Identifying methlyation motifs in nanopore data

Nanomotif

Nanomotif is a Python package that provides functionality for identifying methylation motifs on references using Nanopore sequencing.

Installation

Local Environment

To install Nanomotif in a local Python environment:

python3 -m venv nanomotif
source nanomotif/bin/activate
pip install nanomotif

Conda Environment

If you prefer using Conda for managing your Python environments, you can create a new environment and install Nanomotif as follows:

conda create -n nanomotif python=3.9
conda activate nanomotif
python -m pip install nanomotif

Check installation

Once installed, the installation can be checked by running:

nanomotif check-installation

This runs a test run on a small dataset, ensuring everything works.

Required files

To identify methylated motifs, the following files are required:

• Assembly
• methylation pileup
• Contig-bin relationship*

*Only for bin-consensus (and by extension, complete-workflow)

Assembly

Assembly from any assembler can be used. Nanomotif was developed using assemblies made with metaFlye

Methylation pileup

Generated using ONT modkit. Assembly and basecalls with methylations are required.

OBS: when demultiplexing, trimming of reads may result in errors downstream. We therefore recommend using untrimmed reads for mapping

samtools fastq -T MM,ML {DORADO_BASECALLS.sam} | \
        minimap2 -ax map-ont -y {ASSEMBLY.fasta} - | \
        samtools view -bS | \
        samtools sort -o {ALIGNMENT.bam}
modkit pileup --only-tabs {ALIGNMENT.bam} {OUT.bed}

Contig-bin

File describing which contigs belongs to which bins. It should be headerless, tab-separated file with contig id in the first column and bin in the second column. If the bins are outputted in a folder with one fasta file pr. bin, the contig-bin file can be generated using the following snippet:

BINS=/path/to/bins    # Bin directory
EXT="fa"              # Filename extension
grep ">" ${BINS}/*.${EXT} | \
        sed "s/.*\///" | \
        sed "s/.${EXT}:>/\t/" | \
        awk -F'\t' '{print $2 "\t" $1}' > contig_bin.tsv

Usage

usage: nanomotif [-h] [--version] {find-motifs,score-motifs,bin-consensus,complete-workflow,check-installation} ...

Motif identification and utilisation commands

positional arguments:
                        Command descriptions
    find-motifs         identifies motifs in contigs
    score-motifs        generate feature complete output (all identified motifs have an entry for all contigs)
    bin-consensus       generate consensus set of motif for each bin
    complete-workflow   run find-motifs, score-motifs and bin-consensus

Monoculture

If you are interested in finding methylated motifs in a monoculture sample, we recomment just running find-motifs.

nanomotif find-motifs ASSEMBLY.fasta PILEUP.bed

Metagenomic sample

If you have metagenomic sample with multiple organims, we recommend running complete-workflow

nanomotif complete-workflow ASSEMBLY.fasta PILEUP.bed CONTIG_BIN.tsv

Help

Help page of complete-workflow contains description of all arguments

usage: nanomotif complete-workflow [-h] [--out OUT] [-t THREADS] [-v] [--seed SEED] [--threshold_methylation_general THRESHOLD_METHYLATION_GENERAL]
                                   [--search_frame_size SEARCH_FRAME_SIZE] [--threshold_methylation_confident THRESHOLD_METHYLATION_CONFIDENT]
                                   [--threshold_valid_coverage THRESHOLD_VALID_COVERAGE] [--minimum_kl_divergence MINIMUM_KL_DIVERGENCE]
                                   assembly pileup bins
positional arguments:
  assembly              path to the assembly file.
  pileup                path to the modkit pileup file.
  bins                  tsv file specifying which bin contigs belong.

optional arguments:
  -h, --help            show this help message and exit
  --out OUT             path to the output folder
  -t THREADS, --threads THREADS
                        number of threads to use. Default is 1
  -v, --verbose         increase output verbosity. (set logger to debug level)
  --seed SEED           seed for random number generator. Default: 1
  --threshold_methylation_general THRESHOLD_METHYLATION_GENERAL
                        minimum fraction of reads that must be methylated at a position for the position to be methylated. These position are used for counting number of
                        methylated position of a motif. Default: 0.6
  --search_frame_size SEARCH_FRAME_SIZE
                        length of the sequences sampled around confident methylation sites. Default: 40
  --threshold_methylation_confident THRESHOLD_METHYLATION_CONFIDENT
                        minimum fraction of reads that must be methylated at a position for the position to be considered confiently methylated. These position are used to
                        search for candidate motifs. Default: 0.8
  --threshold_valid_coverage THRESHOLD_VALID_COVERAGE
                        minimum valid base coverage for a position to be considered. Default: 5
  --minimum_kl_divergence MINIMUM_KL_DIVERGENCE
                        minimum KL-divergence for a position to considered for expansion in motif search. Higher value means less exhaustive, but faster search. Default: 0.2

Output description

find-motifs and score-motifs

find-motifs outputs results to motifs.tsv and score-motifs outputs result to motifs-scored.tsv.

find-motifsand score-motifs follow the same output format, described in the table below:

Column	Description
contig	contig in which the motif was found
motif	sequence of the detected motif in IUPAC format
mod_position	position within the motif where the methylation is located. 0-based index.
mod_type	the type of modification [a (6mA) or m (5mC)]
n_mod	number of motif positions that are methylated in the contig
n_nomod	number of motif positions that are not methylated in the contig
motifs_type	type of motif the sequence (palindrome, non-palindrome, bipartite or ambiguous)
motif_complement	Sequence of the complement motif if present in IUPAC format.
mod_position_complement	Position within the complement motif where the methylation is located. 0-based index.
n_mod_complement	Number of motif positions that are methylated in the contig.
n_nomod_complement	Number of motif positions that are not methylated in the contig.

Running find-motifs generates pre-cleanup folder, which contains motif that got removed in the postprocessing steps. The name of the file indicates which postprocessing steps have been run on the motifs.

bin-consensus

bin-consensus outputs results to bin-motifs.tsv The format is almost identical the the output of find-motifs, except everything is aggregated to bin level and the contig column is replaced by a bin column

Column	Description
bin	bin to which the motif belong
motif	sequence of the detected motif in IUPAC format
mod_position	position within the motif where the methylation is located. 0-based index.
mod_type	the type of modification [a (6mA) or m (5mC)]
n_mod	number of motif positions that are methylated in all contigs in the bin
n_nomod	number of motif positions that are not methylated in all contigs in the bin
motifs_type	type of motif the sequence (palindrome, non-palindrome, bipartite or ambiguous)
motif_complement	Sequence of the complement motif if present.
mod_position_complement	Position within the complement motif where the methylation is located. 0-based index.
n_mod_complement	Number of motif positions that are methylated in all contigs in the bin
n_nomod_complement	Number of motif positions that are not methylated in all contigs in the bin

License

Nanomotif is released under the MIT License. Feel free to use, modify, and distribute the package in accordance with the terms of the license.

Acknowledgments

Nanomotif builds upon various open-source libraries and tools that are instrumental in its functionality. We would like to express our gratitude to the developers and contributors of these projects for their valuable work.