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      OCTAVVS: A Graphical Toolbox for High-Throughput Preprocessing and Analysis of Vibrational Spectroscopy Imaging Data

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          Abstract

          Modern vibrational spectroscopy techniques enable the rapid collection of thousands of spectra in a single hyperspectral image, allowing researchers to study spatially heterogeneous samples at micrometer resolution. A number of algorithms have been developed to correct for effects such as atmospheric absorption, light scattering by cellular structures and varying baseline levels. After preprocessing, spectra are commonly decomposed and clustered to reveal informative patterns and subtle spectral changes. Several of these steps are slow, labor-intensive and require programming skills to make use of published algorithms and code. We here present a free and platform-independent graphical toolbox that allows rapid preprocessing of large sets of spectroscopic images, including atmospheric correction and a new algorithm for resonant Mie scattering with improved speed. The software also includes modules for decomposition into constituent spectra using the popular Multivariate Curve Resolution–Alternating Least Squares (MCR-ALS) algorithm, augmented by region-of-interest selection, as well as clustering and cluster annotation.

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          Using Fourier transform IR spectroscopy to analyze biological materials.

          IR spectroscopy is an excellent method for biological analyses. It enables the nonperturbative, label-free extraction of biochemical information and images toward diagnosis and the assessment of cell functionality. Although not strictly microscopy in the conventional sense, it allows the construction of images of tissue or cell architecture by the passing of spectral data through a variety of computational algorithms. Because such images are constructed from fingerprint spectra, the notion is that they can be an objective reflection of the underlying health status of the analyzed sample. One of the major difficulties in the field has been determining a consensus on spectral pre-processing and data analysis. This manuscript brings together as coauthors some of the leaders in this field to allow the standardization of methods and procedures for adapting a multistage approach to a methodology that can be applied to a variety of cell biological questions or used within a clinical setting for disease screening or diagnosis. We describe a protocol for collecting IR spectra and images from biological samples (e.g., fixed cytology and tissue sections, live cells or biofluids) that assesses the instrumental options available, appropriate sample preparation, different sampling modes as well as important advances in spectral data acquisition. After acquisition, data processing consists of a sequence of steps including quality control, spectral pre-processing, feature extraction and classification of the supervised or unsupervised type. A typical experiment can be completed and analyzed within hours. Example results are presented on the use of IR spectra combined with multivariate data processing.
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            Multivariate curve resolution applied to second order data

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              MCR-ALS GUI 2.0: New features and applications

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                Author and article information

                Journal
                Methods Protoc
                Methods Protoc
                mps
                Methods and Protocols
                MDPI
                2409-9279
                01 May 2020
                June 2020
                : 3
                : 2
                : 34
                Affiliations
                [1 ]Department of Astronomy and Theoretical Physics, Lund University, 223 62 Lund, Sweden; syahril.siregar@ 123456thep.lu.se (S.S.); carsten@ 123456thep.lu.se (C.P.)
                [2 ]Department of Biology, Lund University, 223 62 Lund, Sweden; michiel.op_de_beeck@ 123456biol.lu.se (M.O.D.B.); anders.tunlid@ 123456biol.lu.se (A.T.); per.persson@ 123456biol.lu.se (P.P.)
                [3 ]Centre for Environmental and Climate Research (CEC), Lund University, 223 62 Lund, Sweden
                Author notes
                [* ]Correspondence: carl@ 123456thep.lu.se
                Author information
                https://orcid.org/0000-0001-9729-8891
                https://orcid.org/0000-0002-8041-8575
                https://orcid.org/0000-0002-8727-0999
                https://orcid.org/0000-0001-9172-3068
                Article
                mps-03-00034
                10.3390/mps3020034
                7359710
                32369914
                f9db004f-af1d-4b6d-b080-b8da57ab5da1
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 31 March 2020
                : 28 April 2020
                Categories
                Article

                infrared spectroscopy,hyperspectral,atmospheric correction,mie scattering correction,mcr-als

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