图片编号:功能连接和omics分析工具的描述以及确定种族混的案例研究
Anton Orlichenko1, Grant Daly2, Ziyu Zhou1
1Department of Biomedical Engineering, Tulane University, New Orleans, LA, USA.
Neuroimage. Reports
|December 21, 2023
概括
ImageNomer软件有助于分析脑部成像和遗传数据,揭示种族是预测青少年成就的重要因素. 该工具有助于识别和控制神经成像研究中的人口偏差.
科学领域:
- 神经成像是一种神经成像.
- 遗传学 是一个遗传学.
- 数据科学数据科学数据科学
背景情况:
- 功能连接 (FC) 和基因组数据分析往往缺乏用户友好的接口,阻碍了对人口统计学混和质量控制问题的识别.
- FC数据的高维度 (数以万计的特征) 需要有效的可视化来进行探索和分析.
研究的目的:
- 介绍ImageNomer,这是一个基于Python的工具,具有GUI,用于可视化和分析主体和队列级人口,基因组和成像数据.
- 展示ImageNomer在神经成像和遗传数据集中检测混,特别是种族方面的实用性.
主要方法:
- 开发了ImageNomer,这是一个独立的Docker图像,具有基于浏览器的GUI用于数据探索.
- 在费城神经发育队列 (PNC) 和BSNIP数据集中利用ImageNomer进行FC,基因组 (SNP) 和成就得分数据的相关性分析和可视化.
主要成果:
- 在使用PNC数据集中的FC数据预测成就得分时,种族被确定为重要因素.
- 证明了FC和SNP预测成就分数的功能,当种族被控制时,失去了预测能力.
- 在BSNIP数据集中的FC数据中确认种族是强烈的混.
结论:
- ImageNomer提供了一个有效的GUI,用于探索复杂的神经成像和基因组数据集,并检测混变量.
- 种族是功能连接数据中的一个实质性的混,挑战了健康青少年神经成像和遗传研究中与成就相关特征的解释.
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