Nanopore sequencing technology, also known as the third-generation sequencing (TGS) technology, enables real-time single molecular sequencing without polymerase chain reaction (PCR) amplification or chemical labeling. Nanopore sequencing can avoid the introduction of false mutations during experiments and sequencing, ensure high fidelity, and deliver ultra-long reads with lengths in the megabase range. The sequencing speed of some sequencing instruments, such as the MinION from Oxford Nanopore Technologies (ONT), can reach 450 base pairs (bp)/s for DNA and 70 nucleotides (nt)/s for RNA. In recent years, technological innovations in this field have continuously improved sequencing accuracy, read length, and throughput. These breakthroughs, in turn, require the development of experimental and bioinformatics methods that must be integrated to support cutting-edge scientific research using high-resolution methods, modalities, and computations.
Although many bioinformatics tools exist for nanopore sequencing, their adaptability, accuracy, robustness, and efficiency are far from satisfactory. For example, many of the tools used for nanopore sequencing were originally developed for Pacific Biosciences (PacBio) data generated by the Single-Molecule Real-Time (SMRT) sequencing platform. Therefore, parallel computation toolkits specifically and efficiently designed for nanopore sequencing are urgently needed. To date, many specific analyzes of nanopore sequencing data have focused on better use of the ionic current signal for base calling, base modification detection, and polishing. Other tools use long read lengths while allowing for a high error rate for downstream analyzes such as error correction, alignment, assembly, base mutation, and structural variation detection. The extremely large metadata and read information, such as the current signal value, is stored in the binary files in fast5 format, resulting in significant IT costs. Therefore, more cost storage technologies for nanopore sequencing data are also needed.
For the development of new nanopore, parallel advanced high-resolution computational methods tailored to specific applications, we welcome original research articles and reviews on the following topics:
- The algorithm development and optimization of base calling and base modification detection based on nanopore sequencings, such as statistical algorithms and deep learning methods.
- The development and optimization of algorithms for base/signal error correction based on nanopore sequencing.
- The development of bioinformatics data analysis tools based on nanopore sequencings, such as alignment, de novo assembly, variation detection, and metagenomic analysis.
- The development of raw data storage technologies based on nanopore sequencing.
- The relevant research, prospects, and reviews for the application of nanopore sequencing technology.
Nanopore sequencing technology, also known as the third-generation sequencing (TGS) technology, enables real-time single molecular sequencing without polymerase chain reaction (PCR) amplification or chemical labeling. Nanopore sequencing can avoid the introduction of false mutations during experiments and sequencing, ensure high fidelity, and deliver ultra-long reads with lengths in the megabase range. The sequencing speed of some sequencing instruments, such as the MinION from Oxford Nanopore Technologies (ONT), can reach 450 base pairs (bp)/s for DNA and 70 nucleotides (nt)/s for RNA. In recent years, technological innovations in this field have continuously improved sequencing accuracy, read length, and throughput. These breakthroughs, in turn, require the development of experimental and bioinformatics methods that must be integrated to support cutting-edge scientific research using high-resolution methods, modalities, and computations.
Although many bioinformatics tools exist for nanopore sequencing, their adaptability, accuracy, robustness, and efficiency are far from satisfactory. For example, many of the tools used for nanopore sequencing were originally developed for Pacific Biosciences (PacBio) data generated by the Single-Molecule Real-Time (SMRT) sequencing platform. Therefore, parallel computation toolkits specifically and efficiently designed for nanopore sequencing are urgently needed. To date, many specific analyzes of nanopore sequencing data have focused on better use of the ionic current signal for base calling, base modification detection, and polishing. Other tools use long read lengths while allowing for a high error rate for downstream analyzes such as error correction, alignment, assembly, base mutation, and structural variation detection. The extremely large metadata and read information, such as the current signal value, is stored in the binary files in fast5 format, resulting in significant IT costs. Therefore, more cost storage technologies for nanopore sequencing data are also needed.
For the development of new nanopore, parallel advanced high-resolution computational methods tailored to specific applications, we welcome original research articles and reviews on the following topics:
- The algorithm development and optimization of base calling and base modification detection based on nanopore sequencings, such as statistical algorithms and deep learning methods.
- The development and optimization of algorithms for base/signal error correction based on nanopore sequencing.
- The development of bioinformatics data analysis tools based on nanopore sequencings, such as alignment, de novo assembly, variation detection, and metagenomic analysis.
- The development of raw data storage technologies based on nanopore sequencing.
- The relevant research, prospects, and reviews for the application of nanopore sequencing technology.
