Center for Industrial Mathematics, University of Bremen, Bibliothekstr, 1, 28359 Bremen, Germany.
BMC Bioinformatics. 2012;13 Suppl 16(Suppl 16):S11. doi: 10.1186/1471-2105-13-S16-S11. Epub 2012 Nov 5.
Matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) imaging mass spectrometry, also called MALDI-imaging, is a label-free bioanalytical technique used for spatially-resolved chemical analysis of a sample. Usually, MALDI-imaging is exploited for analysis of a specially prepared tissue section thaw mounted onto glass slide. A tremendous development of the MALDI-imaging technique has been observed during the last decade. Currently, it is one of the most promising innovative measurement techniques in biochemistry and a powerful and versatile tool for spatially-resolved chemical analysis of diverse sample types ranging from biological and plant tissues to bio and polymer thin films. In this paper, we outline computational methods for analyzing MALDI-imaging data with the emphasis on multivariate statistical methods, discuss their pros and cons, and give recommendations on their application. The methods of unsupervised data mining as well as supervised classification methods for biomarker discovery are elucidated. We also present a high-throughput computational pipeline for interpretation of MALDI-imaging data using spatial segmentation. Finally, we discuss current challenges associated with the statistical analysis of MALDI-imaging data.
基质辅助激光解吸/电离飞行时间（MALDI-TOF）成像质谱，也称为 MALDI 成像，是一种用于对样品进行空间分辨化学分析的无标记生物分析技术。通常，MALDI-成像用于分析特别制备的组织切片，这些切片解冻后安装在载玻片上。在过去的十年中，MALDI-成像技术得到了极大的发展。目前，它是生物化学中最有前途的创新测量技术之一，也是一种强大而通用的工具，可用于对从生物和植物组织到生物和聚合物薄膜等各种类型的样品进行空间分辨的化学分析。在本文中，我们概述了用于分析 MALDI-成像数据的计算方法，重点是多元统计方法，讨论了它们的优缺点，并就其应用提出了建议。阐述了用于生物标志物发现的无监督数据挖掘方法和有监督分类方法。我们还提出了一种使用空间分割对 MALDI-成像数据进行解释的高通量计算管道。最后，我们讨论了与 MALDI-成像数据的统计分析相关的当前挑战。
