VIPER: a web application for rapid expert review of variant calls

Development and validation of Houston Methodist Variant Viewer version 3: updates to our application for interpretation of next-generation sequencing data

Objectives

Informatics tools that support next-generation sequencing workflows are essential to deliver timely interpretation of somatic variants in cancer. Here, we describe significant updates to our laboratory developed bioinformatics pipelines and data management application termed Houston Methodist Variant Viewer (HMVV).

Materials and Methods

We collected feature requests and workflow improvement suggestions from the end-users of HMVV version 1. Over 1.5 years, we iteratively implemented these features in five sequential updates to HMVV version 3.

Results

We improved the performance and data throughput of the application while reducing the opportunity for manual data entry errors. We enabled end-user workflows for pipeline monitoring, variant interpretation and annotation, and integration with our laboratory information system. System maintenance was improved through enhanced defect reporting, heightened data security, and improved modularity in the code and system environments.

Discussion and Conclusion

Validation of each HMVV update was performed according to expert guidelines. We enabled an 8× reduction in the bioinformatics pipeline computation time for our longest running assay. Our molecular pathologists can interpret the assay results at least 2 days sooner than was previously possible. The application and pipeline code are publicly available at https://github.com/hmvv.

Visualization tools for human structural variations identified by whole-genome sequencing

Visualizing structural variations (SVs) is a critical step for finding associations between SVs and human traits or diseases. Given that there are many sequencing platforms used for SV identification and given that how best to visualize SVs together with other data, such as read alignments and annotations, depends on research goals, there are dozens of SV visualization tools designed for different research goals and sequencing platforms. Here, we provide a comprehensive survey of over 30 SV visualization tools to help users choose which tools to use. This review targets users who wish to visualize a set of SVs identified from the massively parallel sequencing reads of an individual human genome. We first categorize the ways in which SV visualization tools display SVs into ten major categories, which we denote as view modules. View modules allow readers to understand the features of each SV visualization tool quickly. Next, we introduce the features of individual SV visualization tools from several aspects, including whether SV views are integrated with annotations, whether long-read alignment is displayed, whether underlying data structures are graph-based, the type of SVs shown, whether auditing is possible, whether bird's eye view is available, sequencing platforms, and the number of samples. We hope that this review will serve as a guide for readers on the currently available SV visualization tools and lead to the development of new SV visualization tools in the near future.

MoMI-G: modular multi-scale integrated genome graph browser

Background

Genome graph is an emerging approach for representing structural variants on genomes with branches. For example, representing structural variants of cancer genomes as a genome graph is more natural than representing such genomes as differences from the linear reference genome. While more and more structural variants are being identified by long-read sequencing, many of them are difficult to visualize using existing structural variants visualization tools. To this end, visualization method for large genome graphs such as human cancer genome graphs is demanded.

Results

We developed MOdular Multi-scale Integrated Genome graph browser, MoMI-G, a web-based genome graph browser that can visualize genome graphs with structural variants and supporting evidences such as read alignments, read depth, and annotations. This browser allows more intuitive recognition of large, nested, and potentially more complex structural variations. MoMI-G has view modules for different scales, which allow users to view the whole genome down to nucleotide-level alignments of long reads. Alignments spanning reference alleles and those spanning alternative alleles are shown in the same view. Users can customize the view, if they are not satisfied with the preset views. In addition, MoMI-G has Interval Card Deck, a feature for rapid manual inspection of hundreds of structural variants. Herein, we describe the utility of MoMI-G by using representative examples of large and nested structural variations found in two cell lines, LC-2/ad and CHM1.

Conclusions

Users can inspect complex and large structural variations found by long-read analysis in large genomes such as human genomes more smoothly and more intuitively. In addition, users can easily filter out false positives by manually inspecting hundreds of identified structural variants with supporting long-read alignments and annotations in a short time.

Software availability

MoMI-G is freely available at https://github.com/MoMI-G/MoMI-G under the MIT license.