isONform 0.3.0

De novo construction of isoforms from long-read data

isONform - Reference-free isoform reconstruction from long read sequencing data

Table of contents

1. Installation
2. Introduction
3. Output
4. Running isONform
   1. Running a test
5. Credits

Installation

Via pip

pip install isONform

This command installs isONforms dependencies:

1. networkx
2. ordered-set
3. matplotlib
4. parasail
5. edlib
6. pyinstrument
7. namedtuple
8. recordclass

From github source

1. Create a new environment for isONform (at least python 3.7 required):
   conda create -n isonform python=3.10 pip
conda activate isonform
   

2. Install isONcorrect and SPOA
   pip install isONcorrect
conda install -c bioconda spoa
   

3. Install other dependencies of isONform:
   conda install networkx
pip install parasail
   

4. clone this repository

Introduction

IsONform generates isoforms out of clustered and corrected long reads. For this a graph is built up using the networkx api and different simplification strategies are applied to it, such as bubble popping and node merging. The algorithm uses spoa to generate the final isoforms.

Running isONform

To run the algorithm:

python isONform_parallel.py --fastq_folder path/to/input/files --t <nr_cores> --outfolder /path/to/outfolder --split_wrt_batches 

the isON-pipeline (isONclust, isONcorrect, isONform) can be run via:

./full_pipeline.sh <raw_reads.fq>  <outfolder>  <num_cores> <isONform_folder> <iso_abundance> <mode>

(Note that this requires pychopper, isONclust and isONcorrect to be installed)

Contact

If you encounter any problems, please raise an issue on the issues page, you can also contact the developer of this repository via: alexander.petri[at]math.su.se

Credits

Please cite [1] when using isONform.

1. Petri, A. J., & Sahlin, K. (2023). isONform: reference-free transcriptome reconstruction from Oxford Nanopore data. Bioinformatics, 39(Supplement_1), i222-i231. https://academic.oup.com/bioinformatics/article/39/Supplement_1/i222/7210488 .