Visualisation of quadratic discriminant analysis and its application in exploration of microbial interactions

Background When comparing diseased and non-diseased patients in order to discriminate between the aspects associated with the specific disease, it is often observed that the diseased patients have more variability than the non-diseased patients. In such cases Quadratic discriminant analysis is requi...
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Gespeichert in:

Autor*in:	Gardner-Lubbe, Sugnet [verfasserIn] Dube, Felix S

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2015

Schlagwörter:	Quadratic discriminant analysis Canonical variate analysis Biplots

Anmerkung:	© Gardner-Lubbe and Dube; licensee BioMed Central. 2015

Übergeordnetes Werk:	Enthalten in: BioData Mining - London : BioMed Central, 2008, 8(2015), 1 vom: 25. Feb.
Übergeordnetes Werk:	volume:8 ; year:2015 ; number:1 ; day:25 ; month:02

Links:	Volltext

DOI / URN:	10.1186/s13040-015-0041-9

Katalog-ID:	SPR029586879

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520			\|a Background When comparing diseased and non-diseased patients in order to discriminate between the aspects associated with the specific disease, it is often observed that the diseased patients have more variability than the non-diseased patients. In such cases Quadratic discriminant analysis is required which is based on the estimation of different covariance structures for the different groups. Having different covariance matrices means the Canonical variate transformation cannot be used to obtain a visual representation of the discrimination and group separation. Results In this paper an alternative method is proposed: combining the different transformations for the different groups into a single representation of the sample points with classification regions. In order to associate the differences in variables with group discrimination, a biplot is produced which include information on the variables, samples and their relationship.
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spelling	10.1186/s13040-015-0041-9 doi (DE-627)SPR029586879 (SPR)s13040-015-0041-9-e DE-627 ger DE-627 rakwb eng Gardner-Lubbe, Sugnet verfasserin aut Visualisation of quadratic discriminant analysis and its application in exploration of microbial interactions 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Gardner-Lubbe and Dube; licensee BioMed Central. 2015 Background When comparing diseased and non-diseased patients in order to discriminate between the aspects associated with the specific disease, it is often observed that the diseased patients have more variability than the non-diseased patients. In such cases Quadratic discriminant analysis is required which is based on the estimation of different covariance structures for the different groups. Having different covariance matrices means the Canonical variate transformation cannot be used to obtain a visual representation of the discrimination and group separation. Results In this paper an alternative method is proposed: combining the different transformations for the different groups into a single representation of the sample points with classification regions. In order to associate the differences in variables with group discrimination, a biplot is produced which include information on the variables, samples and their relationship. Quadratic discriminant analysis (dpeaa)DE-He213 Canonical variate analysis (dpeaa)DE-He213 Biplots (dpeaa)DE-He213 Dube, Felix S aut Enthalten in BioData Mining London : BioMed Central, 2008 8(2015), 1 vom: 25. Feb. (DE-627)572421893 (DE-600)2438773-3 1756-0381 nnns volume:8 year:2015 number:1 day:25 month:02 https://dx.doi.org/10.1186/s13040-015-0041-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2015 1 25 02
allfields_unstemmed	10.1186/s13040-015-0041-9 doi (DE-627)SPR029586879 (SPR)s13040-015-0041-9-e DE-627 ger DE-627 rakwb eng Gardner-Lubbe, Sugnet verfasserin aut Visualisation of quadratic discriminant analysis and its application in exploration of microbial interactions 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Gardner-Lubbe and Dube; licensee BioMed Central. 2015 Background When comparing diseased and non-diseased patients in order to discriminate between the aspects associated with the specific disease, it is often observed that the diseased patients have more variability than the non-diseased patients. In such cases Quadratic discriminant analysis is required which is based on the estimation of different covariance structures for the different groups. Having different covariance matrices means the Canonical variate transformation cannot be used to obtain a visual representation of the discrimination and group separation. Results In this paper an alternative method is proposed: combining the different transformations for the different groups into a single representation of the sample points with classification regions. In order to associate the differences in variables with group discrimination, a biplot is produced which include information on the variables, samples and their relationship. Quadratic discriminant analysis (dpeaa)DE-He213 Canonical variate analysis (dpeaa)DE-He213 Biplots (dpeaa)DE-He213 Dube, Felix S aut Enthalten in BioData Mining London : BioMed Central, 2008 8(2015), 1 vom: 25. Feb. (DE-627)572421893 (DE-600)2438773-3 1756-0381 nnns volume:8 year:2015 number:1 day:25 month:02 https://dx.doi.org/10.1186/s13040-015-0041-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2015 1 25 02
allfieldsGer	10.1186/s13040-015-0041-9 doi (DE-627)SPR029586879 (SPR)s13040-015-0041-9-e DE-627 ger DE-627 rakwb eng Gardner-Lubbe, Sugnet verfasserin aut Visualisation of quadratic discriminant analysis and its application in exploration of microbial interactions 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Gardner-Lubbe and Dube; licensee BioMed Central. 2015 Background When comparing diseased and non-diseased patients in order to discriminate between the aspects associated with the specific disease, it is often observed that the diseased patients have more variability than the non-diseased patients. In such cases Quadratic discriminant analysis is required which is based on the estimation of different covariance structures for the different groups. Having different covariance matrices means the Canonical variate transformation cannot be used to obtain a visual representation of the discrimination and group separation. Results In this paper an alternative method is proposed: combining the different transformations for the different groups into a single representation of the sample points with classification regions. In order to associate the differences in variables with group discrimination, a biplot is produced which include information on the variables, samples and their relationship. Quadratic discriminant analysis (dpeaa)DE-He213 Canonical variate analysis (dpeaa)DE-He213 Biplots (dpeaa)DE-He213 Dube, Felix S aut Enthalten in BioData Mining London : BioMed Central, 2008 8(2015), 1 vom: 25. Feb. (DE-627)572421893 (DE-600)2438773-3 1756-0381 nnns volume:8 year:2015 number:1 day:25 month:02 https://dx.doi.org/10.1186/s13040-015-0041-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2015 1 25 02
allfieldsSound	10.1186/s13040-015-0041-9 doi (DE-627)SPR029586879 (SPR)s13040-015-0041-9-e DE-627 ger DE-627 rakwb eng Gardner-Lubbe, Sugnet verfasserin aut Visualisation of quadratic discriminant analysis and its application in exploration of microbial interactions 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Gardner-Lubbe and Dube; licensee BioMed Central. 2015 Background When comparing diseased and non-diseased patients in order to discriminate between the aspects associated with the specific disease, it is often observed that the diseased patients have more variability than the non-diseased patients. In such cases Quadratic discriminant analysis is required which is based on the estimation of different covariance structures for the different groups. Having different covariance matrices means the Canonical variate transformation cannot be used to obtain a visual representation of the discrimination and group separation. Results In this paper an alternative method is proposed: combining the different transformations for the different groups into a single representation of the sample points with classification regions. In order to associate the differences in variables with group discrimination, a biplot is produced which include information on the variables, samples and their relationship. Quadratic discriminant analysis (dpeaa)DE-He213 Canonical variate analysis (dpeaa)DE-He213 Biplots (dpeaa)DE-He213 Dube, Felix S aut Enthalten in BioData Mining London : BioMed Central, 2008 8(2015), 1 vom: 25. Feb. (DE-627)572421893 (DE-600)2438773-3 1756-0381 nnns volume:8 year:2015 number:1 day:25 month:02 https://dx.doi.org/10.1186/s13040-015-0041-9 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2015 1 25 02
language	English
source	Enthalten in BioData Mining 8(2015), 1 vom: 25. Feb. volume:8 year:2015 number:1 day:25 month:02
sourceStr	Enthalten in BioData Mining 8(2015), 1 vom: 25. Feb. volume:8 year:2015 number:1 day:25 month:02
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topic_facet	Quadratic discriminant analysis Canonical variate analysis Biplots
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author	Gardner-Lubbe, Sugnet
spellingShingle	Gardner-Lubbe, Sugnet misc Quadratic discriminant analysis misc Canonical variate analysis misc Biplots Visualisation of quadratic discriminant analysis and its application in exploration of microbial interactions
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topic_title	Visualisation of quadratic discriminant analysis and its application in exploration of microbial interactions Quadratic discriminant analysis (dpeaa)DE-He213 Canonical variate analysis (dpeaa)DE-He213 Biplots (dpeaa)DE-He213
topic	misc Quadratic discriminant analysis misc Canonical variate analysis misc Biplots
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title	Visualisation of quadratic discriminant analysis and its application in exploration of microbial interactions
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title_full	Visualisation of quadratic discriminant analysis and its application in exploration of microbial interactions
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title_sort	visualisation of quadratic discriminant analysis and its application in exploration of microbial interactions
title_auth	Visualisation of quadratic discriminant analysis and its application in exploration of microbial interactions
abstract	Background When comparing diseased and non-diseased patients in order to discriminate between the aspects associated with the specific disease, it is often observed that the diseased patients have more variability than the non-diseased patients. In such cases Quadratic discriminant analysis is required which is based on the estimation of different covariance structures for the different groups. Having different covariance matrices means the Canonical variate transformation cannot be used to obtain a visual representation of the discrimination and group separation. Results In this paper an alternative method is proposed: combining the different transformations for the different groups into a single representation of the sample points with classification regions. In order to associate the differences in variables with group discrimination, a biplot is produced which include information on the variables, samples and their relationship. © Gardner-Lubbe and Dube; licensee BioMed Central. 2015
abstractGer	Background When comparing diseased and non-diseased patients in order to discriminate between the aspects associated with the specific disease, it is often observed that the diseased patients have more variability than the non-diseased patients. In such cases Quadratic discriminant analysis is required which is based on the estimation of different covariance structures for the different groups. Having different covariance matrices means the Canonical variate transformation cannot be used to obtain a visual representation of the discrimination and group separation. Results In this paper an alternative method is proposed: combining the different transformations for the different groups into a single representation of the sample points with classification regions. In order to associate the differences in variables with group discrimination, a biplot is produced which include information on the variables, samples and their relationship. © Gardner-Lubbe and Dube; licensee BioMed Central. 2015
abstract_unstemmed	Background When comparing diseased and non-diseased patients in order to discriminate between the aspects associated with the specific disease, it is often observed that the diseased patients have more variability than the non-diseased patients. In such cases Quadratic discriminant analysis is required which is based on the estimation of different covariance structures for the different groups. Having different covariance matrices means the Canonical variate transformation cannot be used to obtain a visual representation of the discrimination and group separation. Results In this paper an alternative method is proposed: combining the different transformations for the different groups into a single representation of the sample points with classification regions. In order to associate the differences in variables with group discrimination, a biplot is produced which include information on the variables, samples and their relationship. © Gardner-Lubbe and Dube; licensee BioMed Central. 2015
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title_short	Visualisation of quadratic discriminant analysis and its application in exploration of microbial interactions
url	https://dx.doi.org/10.1186/s13040-015-0041-9
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Visualisation of quadratic discriminant analysis and its application in exploration of microbial interactions

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Zugang & Verfügbarkeit

Vorhandene Bände

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