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Yokoyama TT, Kasahara M. Visualization tools for human structural variations identified by whole-genome sequencing. J Hum Genet 2020; 65:49-60. [PMID: 31666648 PMCID: PMC8075883 DOI: 10.1038/s10038-019-0687-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2019] [Revised: 09/27/2019] [Accepted: 10/02/2019] [Indexed: 01/02/2023]
Abstract
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.
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Affiliation(s)
- Toshiyuki T Yokoyama
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan
| | - Masahiro Kasahara
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan.
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Cao S, Wylie KM, Wyczalkowski MA, Karpova A, Ley J, Sun S, Mashl RJ, Liang WW, Wang X, Johnson K, DiPersio JF, Gay H, Ratner L, Chen F, Adkins DR, Ding L. Dynamic host immune response in virus-associated cancers. Commun Biol 2019; 2:109. [PMID: 30911684 PMCID: PMC6430765 DOI: 10.1038/s42003-019-0352-3] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2018] [Accepted: 02/07/2019] [Indexed: 02/06/2023] Open
Abstract
Viruses drive carcinogenesis in human cancers through diverse mechanisms that have not been fully elucidated but include promoting immune escape. Here we investigated associations between virus-positivity and immune pathway alteration for 2009 tumors across six virus-related cancer types. Analysis revealed that for 3 of 72 human papillomavirus (HPV)-positive head and neck squamous cell carcinoma (HNSC) the HPV genome integrated in immune checkpoint genes PD-L1 or PD-L2, driving elevated expression in the corresponding gene. In addition to the previously described upregulation of the PD-1 immunosuppressive pathway in Epstein-Barr virus (EBV)-positive stomach tumors, we also observed upregulation of the PD-1 pathway in cytomegalovirus (CMV)-positive tumors. Furthermore, we found signatures of T-cell and B-cell response in HPV-positive HNSC and EBV-positive stomach tumors and HPV-positive HNSC patients were associated with better survival when T-cell signals were detected. Our work reveals that viral infection may recruit immune effector cells, and upregulate PD-1 and CTLA-4 immunosuppressive pathways.
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Affiliation(s)
- Song Cao
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110 USA
- McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108 USA
| | - Kristine M. Wylie
- McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108 USA
- Department of Pediatrics, Washington University in St. Louis, St. Louis, MO 63110 USA
| | - Matt A. Wyczalkowski
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110 USA
- McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108 USA
| | - Alla Karpova
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110 USA
| | - Jessica Ley
- Siteman Cancer Center, Washington University in St. Louis, St. Louis, MO 63110 USA
| | - Sam Sun
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110 USA
- McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108 USA
| | - R. Jay Mashl
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110 USA
- McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108 USA
| | - Wen-Wei Liang
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110 USA
- McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108 USA
| | - Xiaowei Wang
- Department of Radiation Oncology, Washington University in St. Louis, St. Louis, MO 63110 USA
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63110 USA
| | - Kimberly Johnson
- Brown School Master of Public Health Program, Washington University in St. Louis, St. Louis, MO 63130 USA
| | - John F. DiPersio
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110 USA
- Siteman Cancer Center, Washington University in St. Louis, St. Louis, MO 63110 USA
| | - Hiram Gay
- Siteman Cancer Center, Washington University in St. Louis, St. Louis, MO 63110 USA
| | - Lee Ratner
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110 USA
| | - Feng Chen
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110 USA
- Siteman Cancer Center, Washington University in St. Louis, St. Louis, MO 63110 USA
| | - Douglas R. Adkins
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110 USA
- Siteman Cancer Center, Washington University in St. Louis, St. Louis, MO 63110 USA
| | - Li Ding
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110 USA
- McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108 USA
- Siteman Cancer Center, Washington University in St. Louis, St. Louis, MO 63110 USA
- Department of Genetics, Washington University in St. Louis, St. Louis, MO 63110 USA
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Belyeu JR, Nicholas TJ, Pedersen BS, Sasani TA, Havrilla JM, Kravitz SN, Conway ME, Lohman BK, Quinlan AR, Layer RM. SV-plaudit: A cloud-based framework for manually curating thousands of structural variants. Gigascience 2018; 7:5026174. [PMID: 29860504 PMCID: PMC6030999 DOI: 10.1093/gigascience/giy064] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2018] [Accepted: 05/25/2018] [Indexed: 01/21/2023] Open
Abstract
SV-plaudit is a framework for rapidly curating structural variant (SV) predictions. For each SV, we generate an image that visualizes the coverage and alignment signals from a set of samples. Images are uploaded to our cloud framework where users assess the quality of each image using a client-side web application. Reports can then be generated as a tab-delimited file or annotated Variant Call Format (VCF) file. As a proof of principle, nine researchers collaborated for 1 hour to evaluate 1,350 SVs each. We anticipate that SV-plaudit will become a standard step in variant calling pipelines and the crowd-sourced curation of other biological results.Code available at https://github.com/jbelyeu/SV-plauditDemonstration video available at https://www.youtube.com/watch?v=ono8kHMKxDs.
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Affiliation(s)
- Jonathan R Belyeu
- Department of Human Genetics, University of Utah, 15 S 2030 E, Salt Lake City, UT, USA.,USTAR Center for Genetic Discovery, University of Utah, Salt Lake City, UT, USA
| | - Thomas J Nicholas
- Department of Human Genetics, University of Utah, 15 S 2030 E, Salt Lake City, UT, USA.,USTAR Center for Genetic Discovery, University of Utah, Salt Lake City, UT, USA
| | - Brent S Pedersen
- Department of Human Genetics, University of Utah, 15 S 2030 E, Salt Lake City, UT, USA.,USTAR Center for Genetic Discovery, University of Utah, Salt Lake City, UT, USA
| | - Thomas A Sasani
- Department of Human Genetics, University of Utah, 15 S 2030 E, Salt Lake City, UT, USA.,USTAR Center for Genetic Discovery, University of Utah, Salt Lake City, UT, USA
| | - James M Havrilla
- Department of Human Genetics, University of Utah, 15 S 2030 E, Salt Lake City, UT, USA.,USTAR Center for Genetic Discovery, University of Utah, Salt Lake City, UT, USA
| | - Stephanie N Kravitz
- Department of Human Genetics, University of Utah, 15 S 2030 E, Salt Lake City, UT, USA.,USTAR Center for Genetic Discovery, University of Utah, Salt Lake City, UT, USA
| | - Megan E Conway
- Department of Human Genetics, University of Utah, 15 S 2030 E, Salt Lake City, UT, USA
| | - Brian K Lohman
- Department of Human Genetics, University of Utah, 15 S 2030 E, Salt Lake City, UT, USA.,USTAR Center for Genetic Discovery, University of Utah, Salt Lake City, UT, USA
| | - Aaron R Quinlan
- Department of Human Genetics, University of Utah, 15 S 2030 E, Salt Lake City, UT, USA.,USTAR Center for Genetic Discovery, University of Utah, Salt Lake City, UT, USA.,Department of Biomedical Informatics, University of Utah, Salt Lake City, UT, USA
| | - Ryan M Layer
- Department of Human Genetics, University of Utah, 15 S 2030 E, Salt Lake City, UT, USA.,USTAR Center for Genetic Discovery, University of Utah, Salt Lake City, UT, USA
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