A Model-Based Background Adjustment for Oligonucleotide Expression Arrays
寡核苷酸表达芯片的模型化背景校正AI 解读 ↓
← 返回论文列表与筛选
阅读说明
本页整理公开书目信息，不生成学术质量评分。AI 解读根据题名及所注明的摘要或原文片段生成，未完成全文核验，可能有误；具体假设、证明与结论请核对原文。摘要保留来源文本，未经模型改写。
DOI 首次登记不等于接收或发表日期。部分更正、评论等条目没有独立摘要；缺少可靠材料时保留待补状态。
引用量采用 OpenAlex 单条关联记录，不合计多个记录；关联记录可能包含正式发表版本，不等于此版本单独引用。缺失不视为零，引用指标不代表论文质量。
关注作者按书目中的完整姓名匹配，同名和姓名变体需人工辨别。相关论文先按共享细分方向和具体方法排列，再参考通用方法与发表日期。
分类依据与纠错
AI 根据所提供的论文材料归类：摘要研究生物芯片预处理、背景噪声及表达量汇总，未提供与所列计量经济学领域细分直接对应的内容。
反馈分类问题正在核对关联版本…
代码、数据与补充材料
正在核对对应版本的资源…
寡核苷酸表达芯片的模型化背景校正
- 研究问题
- 表达芯片的观测强度受到非特异性杂交和扫描光学噪声影响时，如何校正背景并改善后续基因表达量汇总？
- 方法与思路
- 作者利用探针序列信息建立统计模型并导出背景校正估计量，同时考察不恰当校正对探针层面汇总结果的影响。
- 材料陈述的贡献
- 摘要称该方法在多种实际应用中改善默认校正算法的表现，并提供基于其背景校正程序的表达汇总解决方案。
- 阅读关注点
- 应核对信号与背景的模型设定、序列信息的使用方式，以及性能指标、比较数据和背景校正对汇总步骤的影响。
- 阅读边界
- 仅据版本未注明的 OpenAlex 索引摘要；具体模型和改善幅度未提供，摘要提及的软件当前可用性也未经核验。
原文摘要
High-density oligonucleotide expression arrays are widely used in many areas of biomedical research. Affymetrix GeneChip arrays are the most popular. In the Affymetrix system, a fair amount of further preprocessing and data reduction occurs after the image-processing step. Statistical procedures developed by academic groups have been successful in improving the default algorithms provided by the Affymetrix system. In this article we present a solution to one of the preprocessing steps—background adjustment—based on a formal statistical framework. Our solution greatly improves the performance of the technology in various practical applications. These arrays use short oligonucleotides to probe for genes in an RNA sample. Typically, each gene is represented by 11–20 pairs of oligonucleotide probes. The first component of these pairs is referred to as a perfect match probe and is designed to hybridize only with transcripts from the intended gene (i. e., specific hybridization). However, hybridization by other sequences (i. e., nonspecific hybridization) is unavoidable. Furthermore, hybridization strengths are measured by a scanner that introduces optical noise. Therefore, the observed intensities need to be adjusted to give accurate measurements of specific hybridization. We have found that the default ad hoc adjustment, provided as part of the Affymetrix system, can be improved through the use of estimators derived from a statistical model that uses probe sequence information. A final step in preprocessing is to summarize the probe-level data for each gene to define a measure of expression that represents the amount of the corresponding mRNA species. In this article we illustrate the practical consequences of not adjusting appropriately for the presence of nonspecific hybridization and provide a solution based on our background adjustment procedure. Software that computes our adjustment is available as part of the Bioconductor Project (http://www.bioconductor.org).