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Keywords

cpp forward-backward-algorithm hmm nanopore nanopore-sequencing ont python3 signal-processing
Last synced: 6 months ago · JSON representation ·

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  • Host: GitHub
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  • Language: C++
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cpp forward-backward-algorithm hmm nanopore nanopore-sequencing ont python3 signal-processing
Created almost 3 years ago · Last pushed 6 months ago
Metadata Files
Readme License Citation

README.md

Dynamont

A Dynamic Programming Approach to Segment ONT Signals. Dynamont is a segmentation/resquiggling tool for ONT signals. Dynamont was tested on * RNA002 * RNA004 * DNA R10.4.1 5kHz (I applied the trained transition parameters from the RNA004 model to the DNA R10 models. These should be fine-tuned for the DNA models.)

PyPI - Python Version License: GPL v3 PyPI PyPI - Downloads Anaconda-Server Badge Conda Conda package Conda package

DOI



Installation

Pypi/pip

bash pip install dynamont

Conda

bash conda config --add channels jannessp # to install all dependencies from the correct channel conda create -n dynamont jannessp::dynamont conda activate dynamont

Usage

```bash

segment a dataset

dynamont-resquiggle -r -b --mode basic -o -p

train model

dynamont-train -r -b --mode basic -o -p

choosing a pore will automatically load the default model for that pore, a custom model can be used with the parameter --pore_model

```

Default models:

Output

Dynamont produces a tabular output with the following columns:

| Column Name | Description | |-------------------------|-------------| | readid | Unique identifier for the read. | | signalid | Identifier for the signal corresponding to the read. | | start | Start position of the signal segment in the read. | | end | End position of the signal segment in the read. | | basepos | Reference base position in the genomic sequence. | | base | The detected base at this position. | | motif | The surrounding sequence motif in which the base appears. | | state | The methylation state (or modification state) of the base. | | posterior_probability | Probability assigned to the predicted segment. | | polish | Polished kmer, only available in resquiggle mode. |

Example Output

Below is an example of the output generated by Dynamont:

csv readid,signalid,start,end,basepos,base,motif,state,posterior_probability,polish 476b4ed2-7865-4f81-9f78-82d614fb40a2,476b4ed2-7865-4f81-9f78-82d614fb40a2,12762,12777,53,A,AAAAAAAAA,M,0.12434,NA 476b4ed2-7865-4f81-9f78-82d614fb40a2,476b4ed2-7865-4f81-9f78-82d614fb40a2,12777,12791,52,A,AAAAAAAAA,M,0.12146,NA 476b4ed2-7865-4f81-9f78-82d614fb40a2,476b4ed2-7865-4f81-9f78-82d614fb40a2,12791,12806,51,A,AAAAAAAAA,M,0.11881,NA 476b4ed2-7865-4f81-9f78-82d614fb40a2,476b4ed2-7865-4f81-9f78-82d614fb40a2,12806,12820,50,A,AAAAAAAAA,M,0.11665,NA

Exit-Codes

  • -11: Segmentation fault
  • -9: Out of Memory error. Decrease the number of processes or move to a system with more memory.
  • -6: std::bad_alloc
  • 1: resquiggle mode specific: alignment score (Z) does not match between forward and backward run in preprocessing on signal (T) and read (N).
  • 2: resquiggle mode specific: alignment score (Z) does not match between forward and backward run in preprocessing on signal (T) and error correction (C).
  • 3: Alignment score (Z) does not match between forward and backward pass or is -Infinity
  • 4: Input signal is missing or not found in stdin stream
  • 5: Input read is missing or not found in stdin stream
  • 6: raw file does not exist
  • 7: Invalid model path was provided
  • 8: Provided ONT signal is too short
  • 9: Read is too short
  • 10: Signal is smaller than read
  • 11: Read is smaller than kmerSize of provided pore model
  • 20: Terminated using KeyboardInterrupt (Ctrl + C)

Owner

  • Name: RNA Bioinformatics and Highthroughput Analysis Jena
  • Login: rnajena
  • Kind: user
  • Location: Jena

Citation (CITATION.cff)

cff-version: 1.2.0
message: 'If you use this software, please cite it as below.'
authors:
  - family-names: 'Spangenberg'
    given-names: 'Jannes'
    orcid: 'https://orcid.org/0000-0002-6126-411X'
title: 'dynamont'
version: 0.7.1
identifiers:
  - type: doi
    value: 10.5281/zenodo.15016695
date-released: 2024-11-29

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