VoDEx: a Python library for time annotation and management of volumetric functional imaging data.

IF 4.4 3区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS Bioinformatics Pub Date : 2023-09-02 DOI:10.1093/bioinformatics/btad568
Anna Nadtochiy, Peter Luu, Scott E Fraser, Thai V Truong
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引用次数: 0

Abstract

Summary: In functional imaging studies, accurately synchronizing the time course of experimental manipulations and stimulus presentations with resulting imaging data is crucial for analysis. Current software tools lack such functionality, requiring manual processing of the experimental and imaging data, which is error-prone and potentially non-reproducible. We present VoDEx, an open-source Python library that streamlines the data management and analysis of functional imaging data. VoDEx synchronizes the experimental timeline and events (e.g. presented stimuli, recorded behavior) with imaging data. VoDEx provides tools for logging and storing the timeline annotation, and enables retrieval of imaging data based on specific time-based and manipulation-based experimental conditions.

Availability and implementation: VoDEx is an open-source Python library and can be installed via the "pip install" command. It is released under a BSD license, and its source code is publicly accessible on GitHub (https://github.com/LemonJust/vodex). A graphical interface is available as a napari-vodex plugin, which can be installed through the napari plugins menu or using "pip install." The source code for the napari plugin is available on GitHub (https://github.com/LemonJust/napari-vodex). The software version at the time of submission is archived at Zenodo (version v1.0.18, https://zenodo.org/record/8061531).

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VoDEx:用于体积功能成像数据的时间注释和管理的Python库。
摘要:在功能成像研究中,准确同步实验操作和刺激表现的时间进程与产生的成像数据对于分析至关重要。目前的软件工具缺乏这样的功能,需要手动处理实验和成像数据,这很容易出错,并且可能不可复制。我们介绍了VoDEx,一个开源Python库,它简化了功能成像数据的数据管理和分析。VoDEx将实验时间线和事件(例如,呈现的刺激、记录的行为)与成像数据同步。VoDEx提供了用于记录和存储时间轴注释的工具,并能够基于特定的基于时间和基于操作的实验条件检索成像数据。可用性和实现:VoDEx是一个开源Python库,可以通过“pip-install”命令进行安装。它是在BSD许可证下发布的,其源代码可以在GitHub上公开访问(https://github.com/LemonJust/vodex)。图形界面作为napari vodex插件提供,可以通过napari插件菜单或使用“pip-install”进行安装。napari插件的源代码可在GitHub上获得(https://github.com/LemonJust/napari-vodex)。提交时的软件版本存档在Zenodo(v1.0.18版本,https://zenodo.org/record/8061531)。补充信息:补充数据可在生物信息学在线获取。
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来源期刊
Bioinformatics
Bioinformatics 生物-生化研究方法
CiteScore
11.20
自引率
5.20%
发文量
753
审稿时长
2.1 months
期刊介绍: The leading journal in its field, Bioinformatics publishes the highest quality scientific papers and review articles of interest to academic and industrial researchers. Its main focus is on new developments in genome bioinformatics and computational biology. Two distinct sections within the journal - Discovery Notes and Application Notes- focus on shorter papers; the former reporting biologically interesting discoveries using computational methods, the latter exploring the applications used for experiments.
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