The journal of experimental secondary science最新文献

筛选
英文 中文
Minimizing Systematic Errors in Quantitative High Throughput Screening Data Using Standardization, Background Subtraction, and Non-Parametric Regression. 使用标准化、背景减法和非参数回归最小化定量高通量筛选数据的系统误差。
Mitas Ray, Keith Shockley, Grace Kissling
{"title":"Minimizing Systematic Errors in Quantitative High Throughput Screening Data Using Standardization, Background Subtraction, and Non-Parametric Regression.","authors":"Mitas Ray, Keith Shockley, Grace Kissling","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Quantitative high throughput screening (qHTS) has the potential to transform traditional toxicological testing by greatly increasing throughput and lowering costs on a per chemical basis. However, before qHTS data can be utilized for toxicity assessment, systematic errors such as row, column, cluster, and edge effects in raw data readouts need to be removed. Normalization seeks to minimize effects of systematic errors. Linear (LN) normalization, such as standardization and background removal, minimizes row and column effects. Alternatively, local weighted scatterplot smoothing (LOESS or LO) minimizes cluster effects. Both approaches have been used to normalize large scale data sets in other contexts. A new method is proposed in this paper to combine these two approaches (LNLO) to account for systematic errors within and between experiments. Heat maps illustrate that the LNLO method is more effective in removing systematic error than either the LN or the LO approach alone. All analyses were performed on an estrogen receptor agonist assay data set generated as part of the Tox21 collaboration.</p>","PeriodicalId":91818,"journal":{"name":"The journal of experimental secondary science","volume":"3 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2014-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5102623/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144181474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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×
相关产品
×
本文献相关产品
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:604180095
Book学术官方微信