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arXiv 1606.05360stat.ME
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组学研究中质谱数据分析中的转换、归一化和批次效应

Transformation, normalization and batch effect in the analysis of mass spectrometry data for omics studies

Bart J. A. Mertens

备注：
This is a draft version for a chapter to be published in the new edited volume "Statistical Analysis of Proteomics, Metabolomics, and Lipidomics Data Using Mass Spectrometry" (eds, Datta, S. and Mertens, B. J. A.) to be published by Springer in the new series "Frontiers in Probability and the Statistical Sciences" (anticipated publication year 2016)
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摘要：

数据转换、归一化和批量效应的处理是几乎所有基于光谱学的组学数据分析的关键部分。本文对这三个不同的方面进行了回顾和对比。我们提出了一个系统的概述的关键方法，并严格审查一些常见的程序。本文的大部分灵感来自于基于质谱的实验，但我们的大部分讨论通常都是使用不同的光谱方法进行组学数据。

英文摘要：

Data transformation, normalization and handling of batch effect are a key part of data analysis for almost all spectrometry-based omics data. This paper reviews and contrasts these three distinct aspects. We present a systematic overview of the key approaches and critically review some common procedures. Much of this paper is inspired by mass spectrometry based experimentation, but most of our discussion carries over to omics data using distinct spectrometric approaches generally.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

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