SummaryHere we describe NanoPack, a set of tools developed for visualization and processing of long-read sequencing data from Oxford Nanopore Technologies and Pacific Biosciences.Availability and implementationThe NanoPack tools are written in Python3 and released under the GNU GPL3.0 License. The source code can be found at https://github.com/wdecoster/nanopack, together with links to separate scripts and their documentation. The scripts are compatible with Linux, Mac OS and the MS Windows 10 subsystem for Linux and are available as a graphical user interface, a web service at http://nanoplot.bioinf.be and command line tools.Supplementary information Supplementary data are available at Bioinformatics online.

We sequenced the genome of the Yoruban reference individual NA19240 on the long-read sequencing platform Oxford Nanopore PromethION for evaluation and benchmarking of recently published aligners and germline structural variant calling tools, as well as a comparison with the performance of structural variant calling from short-read sequencing data. The structural variant caller Sniffles after NGMLR or minimap2 alignment provides the most accurate results, but additional confidence or sensitivity can be obtained by a combination of multiple variant callers. Sensitive and fast results can be obtained by minimap2 for alignment and a combination of Sniffles and SVIM for variant identification. We describe a scalable workflow for identification, annotation, and characterization of tens of thousands of structural variants from long-read genome sequencing of an individual or population. By discussing the results of this well-characterized reference individual, we provide an approximation of what can be expected in future long-read sequencing studies aiming for structural variant identification.

Technological limitations have hindered the large-scale genetic investigation of tandem repeats in disease. We show that long-read sequencing with a single Oxford Nanopore Technologies PromethION flow cell per individual achieves 30× human genome coverage and enables accurate assessment of tandem repeats including the 10,000-bp Alzheimer’s disease-associated ABCA7 VNTR. The Guppy “flip-flop” base caller and tandem-genotypes tandem repeat caller are efficient for large-scale tandem repeat assessment, but base calling and alignment challenges persist. We present NanoSatellite, which analyzes tandem repeats directly on electric current data and improves calling of GC-rich tandem repeats, expanded alleles, and motif interruptions.

Here we describe NanoPack, a set of tools developed for visualization and processing of long read sequencing data from Oxford Nanopore Technologies and Pacific Biosciences. Availability and Implementation: The NanoPack tools are written in Python3 and released under the GNU GPL3.0 Licence. The source code can be found at https://github.com/wdecoster/nanopack, together with links to separate scripts and their documentation. The scripts are compatible with Linux, Mac OS and the MS Windows 10 subsystem for linux and are available as a graphical user interface, web service at http://nanoplot.bioinf.be and command line tools. Contact: wouter.decoster@molgen.vib-ua.be

De Roeck et al., PromethION sequencing and tandem repeat characterization 2 Abstract Tandem repeats (TRs) can cause disease through their length, sequence motif interruptions, and nucleotide modifications. For many TRs, however, these features are very difficult -if not impossible -to assess, requiring low-throughput and labor-intensive assays. One example is a VNTR in ABCA7 for which we recently discovered that expanded alleles strongly increase risk of Alzheimer's disease. Here, we investigated the potential of long-read whole genome sequencing to surmount these challenges, using the high-throughput PromethION platform from Oxford Nanopore Technologies. To overcome the limitations of conventional base calling and alignment, we developed an algorithm to study the TR size and sequence directly on raw PromethION current data.We report the long-read sequencing of multiple human genomes (n = 11) using only a single sequencing run and flow cell per individual. With the use of fresh DNA extractions, DNA shearing to approximately 20kb and size selection, we obtained an average output of 70 gigabases (Gb) per flow cell, corresponding to a 21x genome coverage, and a maximum yield of 98 Gb (30x genome coverage). All ABCA7 VNTR alleles, including expansions up to 10,000 bases, were spanned by long sequencing reads, validated by Southern blotting. Classical approaches of TR length estimation suffered from low accuracy, low precision, DNA strand effects and/or inability to call pathogenic repeat expansions. In contrast, our novel NanoSatellite algorithm, which circumvents base calling by using dynamic time warping on raw PromethION current data, achieved more than 90% accuracy and high precision (5.6% relative standard deviation) of TR length estimation, and detected all clinically relevant repeat expansions. In addition, we identified alternative TR sequence motifs with high consistency, allowing determination of TR sequence and distinction of VNTR alleles with homozygous length.In conclusion, we validated the robustness of single-experiment whole genome long-read sequencing on PromethION, a prerequisite for application of long-read sequencing in the clinic. In addition, we outperformed Southern blotting, enabling improved characterization of the role of expanded ABCA7 VNTR alleles in Alzheimer's disease, and opening new opportunities for TR research.

We sequenced the Yoruban NA19240 genome on the long read sequencing platform Oxford Nanopore PromethION for benchmarking and evaluation of recently published aligners and structural variant calling tools. In this work, we determined the precision and recall, present high confidence and high sensitivity call sets of variants and discuss optimal parameters. The aligner Minimap2 and structural variant caller Sniffles are both the most accurate and the most computationally efficient tools in our study. We describe our scalable workflow for identification, annotation, and characterization of tens of thousands of structural variants from long read genome sequencing of an individual or population. By discussing the results of this genome we provide an approximation of what can be expected in future long read sequencing studies aiming for structural variant identification.

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