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部分匹配组学研究的倾向评分方法。

Propensity score method for partially matched omics studies.

作者信息

Kuan Pei-Fen

机构信息

Departments of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY, USA.

出版信息

Cancer Inform. 2014 Oct 29;13(Suppl 7):1-10. doi: 10.4137/CIN.S16352. eCollection 2014.

DOI:10.4137/CIN.S16352
PMID:25535453
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4267441/
Abstract

This paper focuses on the problem of partially matched samples in the presence of confounders. We propose using propensity score matching to adjust for confounding factors for the subset of data with incomplete pairs, followed by integrating the P-values computed from the complete and incomplete paired samples, respectively. Several simulations and a case study on DNA methylation are considered to evaluate the operating characteristics of the proposed method.

摘要

本文聚焦于存在混杂因素时部分匹配样本的问题。我们建议使用倾向得分匹配来调整不完全配对数据子集中的混杂因素，随后分别整合从完全配对和不完全配对样本计算出的P值。通过若干模拟以及一项关于DNA甲基化的案例研究来评估所提方法的操作特性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d891/4267441/f7a8d012839a/cin-suppl.7-2014-001f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d891/4267441/697c7d180da9/cin-suppl.7-2014-001f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d891/4267441/f452961de85c/cin-suppl.7-2014-001f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d891/4267441/f7a8d012839a/cin-suppl.7-2014-001f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d891/4267441/697c7d180da9/cin-suppl.7-2014-001f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d891/4267441/f452961de85c/cin-suppl.7-2014-001f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d891/4267441/f7a8d012839a/cin-suppl.7-2014-001f3.jpg

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Optimal caliper width for propensity score matching of three treatment groups: a Monte Carlo study.最佳卡尺宽度用于三处理组倾向评分匹配：一项蒙特卡罗研究。
PLoS One. 2013 Dec 11;8(12):e81045. doi: 10.1371/journal.pone.0081045. eCollection 2013.
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A simple and robust method for partially matched samples using the p-values pooling approach.
基于代谢组学的胰腺癌诊断生物标志物发现和验证的系统评价。
Metabolomics. 2018 Aug 10;14(8):109. doi: 10.1007/s11306-018-1404-2.
基于 p 值合并法的适用于部分匹配样本的简单而稳健的方法。
Stat Med. 2013 Aug 30;32(19):3247-59. doi: 10.1002/sim.5758. Epub 2013 Feb 17.
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Analysing and interpreting DNA methylation data.分析和解读 DNA 甲基化数据。
Nat Rev Genet. 2012 Oct;13(10):705-19. doi: 10.1038/nrg3273.
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Genome-scale analysis of DNA methylation in lung adenocarcinoma and integration with mRNA expression.肺腺癌中 DNA 甲基化的全基因组分析及其与 mRNA 表达的整合。
Genome Res. 2012 Jul;22(7):1197-211. doi: 10.1101/gr.132662.111. Epub 2012 May 21.
6
Integrating prior knowledge in multiple testing under dependence with applications to detecting differential DNA methylation.在相关性下的多重检验中整合先验知识及其在检测差异DNA甲基化中的应用
Biometrics. 2012 Sep;68(3):774-83. doi: 10.1111/j.1541-0420.2011.01730.x. Epub 2012 Jan 19.
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An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies.倾向得分法在观察性研究中减少混杂效应的介绍
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Optimally weighted Z-test is a powerful method for combining probabilities in meta-analysis.最优加权 Z 检验是一种在荟萃分析中合并概率的强大方法。
J Evol Biol. 2011 Aug;24(8):1836-41. doi: 10.1111/j.1420-9101.2011.02297.x. Epub 2011 May 23.
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Comparing paired vs non-paired statistical methods of analyses when making inferences about absolute risk reductions in propensity-score matched samples.比较配对与非配对统计分析方法在倾向评分匹配样本中进行绝对风险降低推断时的效果。
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Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis.比较微阵列分析中用于定量甲基化水平的 Beta 值法和 M 值法。
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