scFlowVis: Streamlining scRNA-seq Analysis through Visual Design

Yiwen Xing; Stanley Owomero; Sophia Tsoka; Rita Borgo; Alfie Abdul-Rahman

scFlowVis: Streamlining scRNA-seq Analysis through Visual Design

Yiwen Xing, Stanley Owomero, Sophia Tsoka, Rita Borgo, Alfie Abdul-Rahman

Research output: Contribution to conference types › Poster › peer-review

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Abstract

The rise of single-cell RNA sequencing (scRNA-seq) technologies has increased the need for visual analytical tools. Current visualization tools often cater to specific analysis stages rather than the entire pipeline, and many analyses rely on computational notebooks requiring significant programming skills. To address these challenges, we developed scFlowVis, a web-based visualization application designed in collaboration with bioinformatics and biological experts. scFlowVis supports the entire analysis pipeline for scRNA-seq data, providing visualization and interactive assistance throughout the process without programming. It dynamically links panel functionalities, allowing users to explore data attributes, compare parameters, and document workflows visually. The tool can also recommend appropriate visualizations based on data characteristics. Our experiences highlight the challenges and lessons in developing visualization
tools for similar research contexts. scFlowVis has been released on https://github.com/EavanXing0416/scFlowVis.

Original language	English
Publication status	Accepted/In press - Aug 2024
Event	IEEE VIS: Visualization & Visual Analytics 2024 - Duration: 13 Oct 2024 → 18 Oct 2024

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Conference	IEEE VIS: Visualization & Visual Analytics 2024
Period	13/10/2024 → 18/10/2024

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VIS2024Poster_scFlowVis_AbstractAccepted author manuscript, 2.07 MB

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title = "scFlowVis: Streamlining scRNA-seq Analysis through Visual Design",

abstract = "The rise of single-cell RNA sequencing (scRNA-seq) technologies has increased the need for visual analytical tools. Current visualization tools often cater to specific analysis stages rather than the entire pipeline, and many analyses rely on computational notebooks requiring significant programming skills. To address these challenges, we developed scFlowVis, a web-based visualization application designed in collaboration with bioinformatics and biological experts. scFlowVis supports the entire analysis pipeline for scRNA-seq data, providing visualization and interactive assistance throughout the process without programming. It dynamically links panel functionalities, allowing users to explore data attributes, compare parameters, and document workflows visually. The tool can also recommend appropriate visualizations based on data characteristics. Our experiences highlight the challenges and lessons in developing visualizationtools for similar research contexts. scFlowVis has been released on https://github.com/EavanXing0416/scFlowVis.",

author = "Yiwen Xing and Stanley Owomero and Sophia Tsoka and Rita Borgo and Alfie Abdul-Rahman",

year = "2024",

month = aug,

language = "English",

note = "IEEE VIS: Visualization & Visual Analytics 2024 ; Conference date: 13-10-2024 Through 18-10-2024",

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TY - CONF

T1 - scFlowVis: Streamlining scRNA-seq Analysis through Visual Design

AU - Xing, Yiwen

AU - Owomero, Stanley

AU - Tsoka, Sophia

AU - Borgo, Rita

AU - Abdul-Rahman, Alfie

PY - 2024/8

Y1 - 2024/8

N2 - The rise of single-cell RNA sequencing (scRNA-seq) technologies has increased the need for visual analytical tools. Current visualization tools often cater to specific analysis stages rather than the entire pipeline, and many analyses rely on computational notebooks requiring significant programming skills. To address these challenges, we developed scFlowVis, a web-based visualization application designed in collaboration with bioinformatics and biological experts. scFlowVis supports the entire analysis pipeline for scRNA-seq data, providing visualization and interactive assistance throughout the process without programming. It dynamically links panel functionalities, allowing users to explore data attributes, compare parameters, and document workflows visually. The tool can also recommend appropriate visualizations based on data characteristics. Our experiences highlight the challenges and lessons in developing visualizationtools for similar research contexts. scFlowVis has been released on https://github.com/EavanXing0416/scFlowVis.

AB - The rise of single-cell RNA sequencing (scRNA-seq) technologies has increased the need for visual analytical tools. Current visualization tools often cater to specific analysis stages rather than the entire pipeline, and many analyses rely on computational notebooks requiring significant programming skills. To address these challenges, we developed scFlowVis, a web-based visualization application designed in collaboration with bioinformatics and biological experts. scFlowVis supports the entire analysis pipeline for scRNA-seq data, providing visualization and interactive assistance throughout the process without programming. It dynamically links panel functionalities, allowing users to explore data attributes, compare parameters, and document workflows visually. The tool can also recommend appropriate visualizations based on data characteristics. Our experiences highlight the challenges and lessons in developing visualizationtools for similar research contexts. scFlowVis has been released on https://github.com/EavanXing0416/scFlowVis.

M3 - Poster

T2 - IEEE VIS: Visualization & Visual Analytics 2024

Y2 - 13 October 2024 through 18 October 2024

ER -

scFlowVis: Streamlining scRNA-seq Analysis through Visual Design

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