快速参数时 warp 峰列表。

Fast parametric time warping of peak lists.

机构信息

Biometris, Wageningen UR, Wageningen, The Netherlands, Educational Institute for Molecular Sciences and Institute for Molecules and Materials, Radboud University, Nijmegen, The Netherlands.

Biometris, Wageningen UR, Wageningen, The Netherlands, Educational Institute for Molecular Sciences and Institute for Molecules and Materials, Radboud University, Nijmegen, The Netherlands Biometris, Wageningen UR, Wageningen, The Netherlands, Educational Institute for Molecular Sciences and Institute for Molecules and Materials, Radboud University, Nijmegen, The Netherlands.

出版信息

Bioinformatics. 2015 Sep 15;31(18):3063-5. doi: 10.1093/bioinformatics/btv299. Epub 2015 May 13.

DOI:10.1093/bioinformatics/btv299

PMID:25971741

Abstract

UNLABELLED

Alignment of peaks across samples is a difficult but unavoidable step in the data analysis for all analytical techniques containing a separation step like chromatography. Important application examples are the fields of metabolomics and proteomics. Parametric time warping (PTW) has already shown to be very useful in these fields because of the highly restricted form of the warping functions, avoiding overfitting. Here, we describe a new formulation of PTW, working on peak-picked features rather than on complete profiles. Not only does this allow for a much more smooth integration in existing pipelines, it also speeds up the (already among the fastest) algorithm by orders of magnitude. Using two publicly available datasets we show the potential of the new approach. The first set is a LC-DAD dataset of grape samples, and the second an LC-MS dataset of apple extracts.

AVAILABILITY AND IMPLEMENTATION

Parametric time warping of peak lists is implemented in the ptw package, version 1.9.1 and onwards, available from Github (https://github.com/rwehrens/ptw) and CRAN (http://cran.r-project.org). The package also contains a vignette, providing more theoretical details and scripts to reproduce the results below.

CONTACT

ron.wehrens@wur.nl.

摘要

未标记

在包含分离步骤（如色谱法）的所有分析技术的数据分析中，对齐样本峰是一个困难但不可避免的步骤。重要的应用实例是代谢组学和蛋白质组学领域。由于翘曲函数的高度限制形式，参数时间扭曲 (PTW) 已经在这些领域显示出非常有用，避免了过度拟合。在这里，我们描述了一种新的 PTW 配方，它基于峰挑选特征而不是完整的轮廓。这不仅允许在现有的管道中进行更平滑的集成，而且还可以将（已经是最快的算法之一）的速度提高几个数量级。我们使用两个公开可用的数据集展示了新方法的潜力。第一个数据集是 LC-DAD 葡萄样本数据集，第二个是 LC-MS 苹果提取物数据集。