p值直方图:推断和诊断。

Q2 Biochemistry, Genetics and Molecular Biology High-Throughput Pub Date : 2018-08-31 DOI:10.3390/ht7030023

Patrick Breheny, Arnold Stromberg, Joshua Lambert

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引用次数: 22

摘要

涉及大量假设检验的生物学和医学实验越来越普遍。可视化这些测试的自然图形方法是从这些测试的p值构造一个直方图。在本文中，我们研究了这些直方图可以呈现的形状，包括规则和不规则的形状，并提出了简单的推理程序，有助于从诊断实验潜在问题的角度解释这些形状。我们详细研究了这些问题的潜在原因，并讨论了可能的补救措施。在整个过程中，提供了不规则的p值直方图的例子，并基于涉及真实生物实验的案例研究。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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p-Value Histograms: Inference and Diagnostics.

It is increasingly common for experiments in biology and medicine to involve large numbers of hypothesis tests. A natural graphical method for visualizing these tests is to construct a histogram from the p-values of these tests. In this article, we examine the shapes, both regular and irregular, that these histograms can take on, as well as present simple inferential procedures that help to interpret the shapes in terms of diagnosing potential problems with the experiment. We examine potential causes of these problems in detail, and discuss potential remedies. Throughout, examples of irregular-looking p-value histograms are provided and based on case studies involving real biological experiments.

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来源期刊

High-Throughput Biochemistry, Genetics and Molecular Biology-Biotechnology

CiteScore

3.60

自引率

0.00%

发文量

审稿时长

9 weeks

期刊介绍： High-Throughput (formerly Microarrays, ISSN 2076-3905) is a multidisciplinary peer-reviewed scientific journal that provides an advanced forum for the publication of studies reporting high-dimensional approaches and developments in Life Sciences, Chemistry and related fields. Our aim is to encourage scientists to publish their experimental and theoretical results based on high-throughput techniques as well as computational and statistical tools for data analysis and interpretation. The full experimental or methodological details must be provided so that the results can be reproduced. There is no restriction on the length of the papers. High-Throughput invites submissions covering several topics, including, but not limited to: -Microarrays -DNA Sequencing -RNA Sequencing -Protein Identification and Quantification -Cell-based Approaches -Omics Technologies -Imaging -Bioinformatics -Computational Biology/Chemistry -Statistics -Integrative Omics -Drug Discovery and Development -Microfluidics -Lab-on-a-chip -Data Mining -Databases -Multiplex Assays