Vibrational spectroscopic image analysis of biological material using multivariate curve resolution-alternating least squares (MCR-ALS).
Identifieur interne : 001A64 ( Main/Exploration ); précédent : 001A63; suivant : 001A65Vibrational spectroscopic image analysis of biological material using multivariate curve resolution-alternating least squares (MCR-ALS).
Auteurs : Judith Felten [Suède] ; Hardy Hall [Suède] ; Joaquim Jaumot [Espagne] ; Romà Tauler [Espagne] ; Anna De Juan [Espagne] ; András Gorzsás [Suède]Source :
- Nature protocols [ 1750-2799 ] ; 2015.
Descripteurs français
- KwdFr :
- Analyse multifactorielle (MeSH), Analyse spectrale Raman (MeSH), Animaux (MeSH), Ilots pancréatiques (composition chimique), Interface utilisateur (MeSH), Méthode des moindres carrés (MeSH), Populus (composition chimique), Souris de lignée C57BL (MeSH), Spectroscopie infrarouge à transformée de Fourier (MeSH), Traitement d'image par ordinateur (méthodes), Xylème (composition chimique).
- MESH :
English descriptors
- KwdEn :
- Animals (MeSH), Image Processing, Computer-Assisted (methods), Islets of Langerhans (chemistry), Least-Squares Analysis (MeSH), Mice, Inbred C57BL (MeSH), Multivariate Analysis (MeSH), Populus (chemistry), Spectroscopy, Fourier Transform Infrared (MeSH), Spectrum Analysis, Raman (MeSH), User-Computer Interface (MeSH), Xylem (chemistry).
- MESH :
Abstract
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 <30-60 min per image), and they are easy to interpret and evaluate both in terms of chemistry and biology, making the method generally more powerful than principal component analysis (PCA) or heat maps of single-band intensities. In addition, chemical and biological evaluation of the results by means of reference matching and segmentation maps (based on k-means clustering) is possible.
DOI: 10.1038/nprot.2015.008
PubMed: 25569330
Affiliations:
Links toward previous steps (curation, corpus...)
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(chemistry)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Analyse multifactorielle (MeSH)</term><term>Analyse spectrale Raman (MeSH)</term><term>Animaux (MeSH)</term><term>Ilots pancréatiques (composition chimique)</term><term>Interface utilisateur (MeSH)</term><term>Méthode des moindres carrés (MeSH)</term><term>Populus (composition chimique)</term><term>Souris de lignée C57BL (MeSH)</term><term>Spectroscopie infrarouge à transformée de Fourier (MeSH)</term><term>Traitement d'image par ordinateur (méthodes)</term><term>Xylème (composition chimique)</term></keywords><keywords scheme="MESH" qualifier="chemistry" xml:lang="en"><term>Islets of Langerhans</term><term>Populus</term><term>Xylem</term></keywords><keywords scheme="MESH" qualifier="composition chimique" xml:lang="fr"><term>Ilots pancréatiques</term><term>Populus</term><term>Xylème</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Image Processing, Computer-Assisted</term></keywords><keywords scheme="MESH" qualifier="méthodes" xml:lang="fr"><term>Traitement d'image par ordinateur</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Animals</term><term>Least-Squares Analysis</term><term>Mice, Inbred C57BL</term><term>Multivariate Analysis</term><term>Spectroscopy, Fourier Transform Infrared</term><term>Spectrum Analysis, Raman</term><term>User-Computer Interface</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Analyse multifactorielle</term><term>Analyse spectrale Raman</term><term>Animaux</term><term>Interface utilisateur</term><term>Méthode des moindres carrés</term><term>Souris de lignée C57BL</term><term>Spectroscopie infrarouge à transformée de Fourier</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">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 <30-60 min per image), and they are easy to interpret and evaluate both in terms of chemistry and biology, making the method generally more powerful than principal component analysis (PCA) or heat maps of single-band intensities. In addition, chemical and biological evaluation of the results by means of reference matching and segmentation maps (based on k-means clustering) is possible. </div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">25569330</PMID><DateCompleted><Year>2015</Year><Month>09</Month><Day>28</Day></DateCompleted><DateRevised><Year>2018</Year><Month>11</Month><Day>13</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1750-2799</ISSN><JournalIssue CitedMedium="Internet"><Volume>10</Volume><Issue>2</Issue><PubDate><Year>2015</Year><Month>Feb</Month></PubDate></JournalIssue><Title>Nature protocols</Title><ISOAbbreviation>Nat Protoc</ISOAbbreviation></Journal><ArticleTitle>Vibrational spectroscopic image analysis of biological material using multivariate curve resolution-alternating least squares (MCR-ALS).</ArticleTitle><Pagination><MedlinePgn>217-40</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1038/nprot.2015.008</ELocationID><Abstract><AbstractText>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 <30-60 min per image), and they are easy to interpret and evaluate both in terms of chemistry and biology, making the method generally more powerful than principal component analysis (PCA) or heat maps of single-band intensities. In addition, chemical and biological evaluation of the results by means of reference matching and segmentation maps (based on k-means clustering) is possible. </AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Felten</LastName><ForeName>Judith</ForeName><Initials>J</Initials><AffiliationInfo><Affiliation>Umeå Plant Science Centre, Department of Forest Genetics and Plant Physiology, Swedish University of Agricultural Sciences, Umeå, Sweden.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Hall</LastName><ForeName>Hardy</ForeName><Initials>H</Initials><AffiliationInfo><Affiliation>Umeå Plant Science Centre, Department of Forest Genetics and Plant Physiology, Swedish University of Agricultural Sciences, Umeå, Sweden.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Jaumot</LastName><ForeName>Joaquim</ForeName><Initials>J</Initials><AffiliationInfo><Affiliation>Institut de Diagnòstic Ambiental i Estudis de l'Aigua-Consejo Superior de Investigaciones Científicas (IDAEA-CSIC), Barcelona, Spain.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Tauler</LastName><ForeName>Romà</ForeName><Initials>R</Initials><AffiliationInfo><Affiliation>Institut de Diagnòstic Ambiental i Estudis de l'Aigua-Consejo Superior de Investigaciones Científicas (IDAEA-CSIC), Barcelona, Spain.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>de Juan</LastName><ForeName>Anna</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>Chemometrics Group, Department of Analytical Chemistry, Universitat de Barcelona, Barcelona, Spain.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Gorzsás</LastName><ForeName>András</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>Department of Chemistry, Umeå University, Umeå, Sweden.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2015</Year><Month>01</Month><Day>08</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>Nat Protoc</MedlineTA><NlmUniqueID>101284307</NlmUniqueID><ISSNLinking>1750-2799</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><CommentsCorrectionsList><CommentsCorrections RefType="ErratumIn"><RefSource>Nat Protoc. 2019 Oct;14(10):3032</RefSource><PMID Version="1">31168086</PMID></CommentsCorrections></CommentsCorrectionsList><MeshHeadingList><MeshHeading><DescriptorName UI="D000818" MajorTopicYN="N">Animals</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D007091" MajorTopicYN="N">Image Processing, Computer-Assisted</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="Y">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D007515" MajorTopicYN="N">Islets of Langerhans</DescriptorName><QualifierName UI="Q000737" MajorTopicYN="N">chemistry</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D016018" MajorTopicYN="N">Least-Squares Analysis</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008810" MajorTopicYN="N">Mice, Inbred C57BL</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D015999" MajorTopicYN="Y">Multivariate Analysis</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D032107" MajorTopicYN="N">Populus</DescriptorName><QualifierName UI="Q000737" MajorTopicYN="N">chemistry</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D017550" MajorTopicYN="Y">Spectroscopy, Fourier Transform Infrared</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D013059" MajorTopicYN="Y">Spectrum Analysis, Raman</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D014584" MajorTopicYN="N">User-Computer 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uniqKey="Jaumot J" first="Joaquim" last="Jaumot">Joaquim Jaumot</name></region><name sortKey="De Juan, Anna" sort="De Juan, Anna" uniqKey="De Juan A" first="Anna" last="De Juan">Anna De Juan</name><name sortKey="Tauler, Roma" sort="Tauler, Roma" uniqKey="Tauler R" first="Romà" last="Tauler">Romà Tauler</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Bois/explor/PoplarV1/Data/Main/Exploration
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|texte= Vibrational spectroscopic image analysis of biological material using multivariate curve resolution-alternating least squares (MCR-ALS).
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