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LongQC: A Quality Control Tool for Third Generation Sequencing Long Read Data.

Yoshinori Fukasawa¹, Luca Ermini², Hai Wang²

¹King Abdullah University of Science and Technology (KAUST), Core Labs, Thuwal, Makkah, Saudi Arabia, 23955-6900 yoshinori.fukasawa@kaust.edu.sa nicole.cheung@kaust.edu.sa.

G3 (Bethesda, Md.)

|February 12, 2020

Summary

This summary is machine-generated.

LongQC is a new automated tool for quality control of long-read genomic data from third generation sequencing (TGS) platforms like Oxford Nanopore and PacBio. It quickly processes and visualizes key statistics for improved data analysis.

Keywords:

Long read Oxford Nanopore PacBio Quality control third generation sequencers

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Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

Third generation sequencing (TGS) technologies, including Oxford Nanopore (ONT) and PacBio SMRT sequencing, produce long-read genomic data.
Quality control (QC) is essential for accurate analysis of TGS data, but existing tools may not be optimized for long reads.

Purpose of the Study:

To introduce LongQC, an automated and user-friendly quality control tool specifically designed for long-read genomic datasets.
To provide optimized key statistics and visualizations for major TGS platforms.

Main Methods:

Development of LongQC, an automated software tool.
Optimization of quality control statistics tailored for long-read sequencing data.
Implementation of automated data processing and visualization functionalities.

Main Results:

LongQC offers an easy and automated solution for quality control of genomic datasets from TGS platforms.
The tool covers major TGS platforms, including Oxford Nanopore Technologies (ONT) and Pacific Biosciences (PacBio).
LongQC efficiently processes and visualizes key statistics relevant to long-read data.

Conclusions:

LongQC provides a valuable and efficient tool for researchers working with long-read sequencing data.
Automated QC with LongQC can streamline genomic data analysis workflows.
The tool enhances the reliability and interpretability of TGS-generated genomic datasets.