The Role of Visualization in Genomics Data Analysis Workflows: The Interviews

Sehi L'Yi; Qianwen Wang; Nils Gehlenborg

doi:10.1109/VIS54172.2023.00029

The Role of Visualization in Genomics Data Analysis Workflows: The Interviews

Sehi L'Yi, Qianwen Wang, Nils Gehlenborg

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

The diversity of genome-mapped data and analysis tasks makes it challenging for a single visualization tool to fulfill all visualization needs. To design a visualization tool that supports various genomics workflows of users, it is critical to first gain insights into the diverse workflows and the limitations of existing genomics tools for supporting them. In this paper, we conducted semi-structured interviews (N=9) to understand the role of visualization in genomics data analysis workflows. Our main goals were to identify various genomics workflows, from data analysis to visual exploration and presentation, and to observe challenges that genomics analysts encounter in these workflows when using existing tools. Through the interviews, we found several unique characteristics of genomics workflows, such as the use of multiple visualization tools and many repetitive tasks, which can significantly affect the overall performance. Based on our findings, we discuss implications for designing effective visualization authoring tools that tightly support genomics workflows, such as supporting automation and reproducibility.

Original language	English (US)
Title of host publication	Proceedings - 2023 IEEE Visualization Conference - Short Papers, VIS 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	101-105
Number of pages	5
ISBN (Electronic)	9798350325577
DOIs	https://doi.org/10.1109/VIS54172.2023.00029
State	Published - 2023
Externally published	Yes
Event	2023 IEEE Visualization Conference, VIS 2023 - Hybrid, Melbourne, Australia Duration: Oct 22 2023 → Oct 27 2023

Publication series

Name	Proceedings - 2023 IEEE Visualization Conference - Short Papers, VIS 2023

Conference

Conference	2023 IEEE Visualization Conference, VIS 2023
Country/Territory	Australia
City	Hybrid, Melbourne
Period	10/22/23 → 10/27/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

H.5.2 [Information Systems]: Information Interfaces and Presentation (e.g., HCI)
User Interfaces

Publisher link

10.1109/VIS54172.2023.00029

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Cite this

L'Yi, S., Wang, Q., & Gehlenborg, N. (2023). The Role of Visualization in Genomics Data Analysis Workflows: The Interviews. In Proceedings - 2023 IEEE Visualization Conference - Short Papers, VIS 2023 (pp. 101-105). (Proceedings - 2023 IEEE Visualization Conference - Short Papers, VIS 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/VIS54172.2023.00029

The Role of Visualization in Genomics Data Analysis Workflows: The Interviews. / L'Yi, Sehi; Wang, Qianwen; Gehlenborg, Nils.
Proceedings - 2023 IEEE Visualization Conference - Short Papers, VIS 2023. Institute of Electrical and Electronics Engineers Inc., 2023. p. 101-105 (Proceedings - 2023 IEEE Visualization Conference - Short Papers, VIS 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

L'Yi, S, Wang, Q & Gehlenborg, N 2023, The Role of Visualization in Genomics Data Analysis Workflows: The Interviews. in Proceedings - 2023 IEEE Visualization Conference - Short Papers, VIS 2023. Proceedings - 2023 IEEE Visualization Conference - Short Papers, VIS 2023, Institute of Electrical and Electronics Engineers Inc., pp. 101-105, 2023 IEEE Visualization Conference, VIS 2023, Hybrid, Melbourne, Australia, 10/22/23. https://doi.org/10.1109/VIS54172.2023.00029

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abstract = "The diversity of genome-mapped data and analysis tasks makes it challenging for a single visualization tool to fulfill all visualization needs. To design a visualization tool that supports various genomics workflows of users, it is critical to first gain insights into the diverse workflows and the limitations of existing genomics tools for supporting them. In this paper, we conducted semi-structured interviews (N=9) to understand the role of visualization in genomics data analysis workflows. Our main goals were to identify various genomics workflows, from data analysis to visual exploration and presentation, and to observe challenges that genomics analysts encounter in these workflows when using existing tools. Through the interviews, we found several unique characteristics of genomics workflows, such as the use of multiple visualization tools and many repetitive tasks, which can significantly affect the overall performance. Based on our findings, we discuss implications for designing effective visualization authoring tools that tightly support genomics workflows, such as supporting automation and reproducibility.",

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author = "Sehi L'Yi and Qianwen Wang and Nils Gehlenborg",

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The Role of Visualization in Genomics Data Analysis Workflows: The Interviews

Abstract

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