TopoQual polishes Pacific Biosciences (PacBio) Circular Consensus Sequencing (CCS) data and accurately predicts quality scores.

Rust 1.65.0+ and Python 3.9+ should be installed. The following programs/packages are required for topoqual to run properly,

• samtools - to read the subread bam file.
• pytorch - to evalute the quality scores using the deeplearning model.
• numpy - for computation.
• pysam - for writing the modified bam file in python.

you can install samtools, pytorch using conda and numpy, pysam using pip:

conda install bioconda::samtools
conda install pytorch::pytorch torchvision torchaudio -c pytorch
pip install pysam
pip install numpy

Download the repository.

git clone https://github.com/lorewar2/TopoQual.git

Configure the thread count in script.sh (Decrease/Increase the thread count depending on the memory availability, 1 thread requires ~10GB of memory)

TEST DATA:

Run the test sample with Topoqual

bash script.sh

REAL DATA:

Modify input/ouput variables to point to your data in script.sh

Run the real sample with Topoqual

bash script.sh

If you are using TopoQual in your work, please cite:

TopoQual polishes circular consensus sequencing data and accurately predicts quality scores