Batch Correction and Harmonization of -Omics Datasets with a Tunable Median Polish of Ratio.

Eric B Dammer, Nicholas T Seyfried, Erik C B Johnson
{"title":"Batch Correction and Harmonization of -Omics Datasets with a Tunable Median Polish of Ratio.","authors":"Eric B Dammer,&nbsp;Nicholas T Seyfried,&nbsp;Erik C B Johnson","doi":"10.3389/fsysb.2023.1092341","DOIUrl":null,"url":null,"abstract":"<p><p>Large scale -omics datasets can provide new insights into normal and disease-related biology when analyzed through a systems biology framework. However, technical artefacts present in most -omics datasets due to variations in sample preparation, batching, platform settings, personnel, and other experimental procedures prevent useful analyses of such data without prior adjustment for these technical factors. Here, we demonstrate a tunable median polish of ratio (TAMPOR) approach for batch effect correction and agglomeration of multiple, multi-batch, site-specific cohorts into a single analyte abundance data matrix that is suitable for systems biology analyses. We illustrate the utility and versatility of TAMPOR through four distinct use cases where the method has been applied to different proteomic datasets, some of which contain a specific defect that must be addressed prior to analysis. We compare quality control metrics and sources of variance before and after application of TAMPOR to show that TAMPOR is effective at removing batch effects and other unwanted sources of variance in -omics data. We also show how TAMPOR can be used to harmonize -omics datasets even when the data are acquired using different analytical approaches. TAMPOR is a powerful and flexible approach for cleaning and harmonization of -omics data prior to downstream systems biology analysis.</p>","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":"3 ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10137904/pdf/nihms-1893744.pdf","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in systems biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/fsysb.2023.1092341","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

Large scale -omics datasets can provide new insights into normal and disease-related biology when analyzed through a systems biology framework. However, technical artefacts present in most -omics datasets due to variations in sample preparation, batching, platform settings, personnel, and other experimental procedures prevent useful analyses of such data without prior adjustment for these technical factors. Here, we demonstrate a tunable median polish of ratio (TAMPOR) approach for batch effect correction and agglomeration of multiple, multi-batch, site-specific cohorts into a single analyte abundance data matrix that is suitable for systems biology analyses. We illustrate the utility and versatility of TAMPOR through four distinct use cases where the method has been applied to different proteomic datasets, some of which contain a specific defect that must be addressed prior to analysis. We compare quality control metrics and sources of variance before and after application of TAMPOR to show that TAMPOR is effective at removing batch effects and other unwanted sources of variance in -omics data. We also show how TAMPOR can be used to harmonize -omics datasets even when the data are acquired using different analytical approaches. TAMPOR is a powerful and flexible approach for cleaning and harmonization of -omics data prior to downstream systems biology analysis.

具有可调中值抛光比率的组学数据集的批量校正和协调。
当通过系统生物学框架进行分析时,大规模组学数据集可以为正常和疾病相关生物学提供新的见解。然而,由于样品制备、批处理、平台设置、人员和其他实验程序的变化,大多数组学数据集中存在技术人工因素,如果没有事先调整这些技术因素,就无法对这些数据进行有用的分析。在这里,我们展示了一种可调的比例中值抛光(TAMPOR)方法,用于批量效应校正和将多个,多批次,特定位点的队列聚集到一个适合系统生物学分析的单一分析物丰度数据矩阵中。我们通过四个不同的用例来说明TAMPOR的实用性和多功能性,其中该方法已应用于不同的蛋白质组学数据集,其中一些包含必须在分析之前解决的特定缺陷。我们比较了使用TAMPOR前后的质量控制指标和方差来源,表明TAMPOR在消除组学数据中的批效应和其他不需要的方差来源方面是有效的。我们还展示了TAMPOR如何用于协调组学数据集,即使数据是使用不同的分析方法获得的。TAMPOR是一种强大而灵活的方法,用于在下游系统生物学分析之前清洁和协调组学数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信