Vibrational spectroscopic image analysis of biological material using multivariate curve resolution-alternating least squares (MCR-ALS)
Vibrational spectroscopic image analysis of biological material using multivariate curve resolution-alternating least squares (MCR-ALS)
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DOI：
10.1038/nprot.2015.008
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发表时间：
2015-02-01
期刊：
影响因子：
14.8
通讯作者：
Gorzsas, Andras
中科院分区：
文献类型：
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作者：
Felten, Judith;Hall, Hardy;Gorzsas, Andras
生物材料(组织切片)的拉曼和傅里叶变换红外(FTIR)显微光谱图像包含有关其化学成分的详细信息。挑战在于确定化学成分的变化，以及定位这些变化并将其分配给不同的条件(病理学、解剖学、环境或遗传因素)。多变量数据分析技术是从数据中解密此类信息的理想选择。该协议提供了一个用户友好的管道和图形用户界面(GUI)，用于通过多变量曲线分辨率-交替最小二乘(MCR-ALS)分析对数据进行预处理，并将像素光谱分解为其贡献的纯成分。该分析考虑了完整的光谱分布，以便识别化合物并可视化它们在样品中的分布，从而对化学上不同的区域进行分类。很快就会取得成果(通常
Raman and Fourier transform IR (FTIR) microspectroscopic images of biological material (tissue sections) contain detailed information about their chemical composition. The challenge lies in identifying changes in chemical composition, as well as locating and assigning these changes to different conditions (pathology, anatomy, environmental or genetic factors). Multivariate data analysis techniques are ideal for decrypting such information from the data. This protocol provides a user-friendly pipeline and graphical user interface (GUI) for data pre-processing and unmixing of pixel spectra into their contributing pure components by multivariate curve resolution-alternating least squares (MCR-ALS) analysis. The analysis considers the full spectral profile in order to identify the chemical compounds and to visualize their distribution across the sample to categorize chemically distinct areas. Results are rapidly achieved (usually