Integration and holistic analysis of multiple multidimensional soil data sets

Complex matrices such as soil have a range of measurable characteristics, and thus data to describe them can be considered multidimensional. These characteristics can be strongly influenced by factors that introduce confounding effects that hinder analyses. Traditional statistical approaches lack th...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Talanta (Oxford) Jg. 274; S. 125954
Hauptverfasser:	Pilkington, Lisa I., Kerner, William, Bertoldi, Daniela, Larcher, Roberto, Lee, Soon A., Goddard, Matthew R., Albanese, Davide, Franceschi, Pietro, Fedrizzi, Bruno
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Netherlands Elsevier B.V 01.07.2024
Schlagworte:	biodiversity biomarkers chemical composition Compositional data Confounding variables data collection fungi metagenomics New Zealand soil Soil analysis Statistical workflow Variable association Variable transformation vineyards viticulture New Zealand Statistical workflow Confounding variables Soil analysis Variable association Variable transformation Compositional data
ISSN:	0039-9140, 1873-3573, 1873-3573
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Abstract	Complex matrices such as soil have a range of measurable characteristics, and thus data to describe them can be considered multidimensional. These characteristics can be strongly influenced by factors that introduce confounding effects that hinder analyses. Traditional statistical approaches lack the flexibility and granularity required to adequately evaluate such matrices, particularly those with large dataset of varying data types (i.e. quantitative non-compositional, quantitative compositional). We present a statistical workflow designed to effectively analyse complex, multidimensional systems, even in the presence of confounding variables. The developed methodology involves exploratory analysis to identify the presence of confounding variables, followed by data decomposition (including strategies for both compositional and non-compositional quantitative data) to minimise the influence of these confounding factors such as sampling site/location. These data processing methods then allow for common patterns to be highlighted in the data, including the identification of biomarkers and determination of non-trivial associations between variables. We demonstrate the utility of this statistical workflow by jointly analysing the chemical composition and fungal biodiversity of New Zealand vineyard soils that have been managed with either organic low-input or conventional input approaches. By applying this pipeline, we were able to identify biomarkers that distinguish viticultural soil from both approaches and also unearth links and associations between the chemical and metagenomic profiles. While soil is an example of a system that can require this type of statistical methodology, there are a range of biological and ecological systems that are challenging to analyse due to the complex interplay of global and local effects. Utilising our developed pipeline will greatly enhance the way that these systems can be studied and the quality and impact of insight gained from their analysis. [Display omitted] •Novel statistical workflow to effectively analyse complex, multidimensional systems.•Methods allow identification of biomarker and non-trivial variable associations.•Workflow demonstrated through analysing New Zealand vineyard soils.•Utility shown by jointly analysing chemical composition and fungal biodiversity.•Developed pipeline will enhance analysis of other complex multidimensional systems.
AbstractList	Complex matrices such as soil have a range of measurable characteristics, and thus data to describe them can be considered multidimensional. These characteristics can be strongly influenced by factors that introduce confounding effects that hinder analyses. Traditional statistical approaches lack the flexibility and granularity required to adequately evaluate such matrices, particularly those with large dataset of varying data types (i.e. quantitative non-compositional, quantitative compositional). We present a statistical workflow designed to effectively analyse complex, multidimensional systems, even in the presence of confounding variables. The developed methodology involves exploratory analysis to identify the presence of confounding variables, followed by data decomposition (including strategies for both compositional and non-compositional quantitative data) to minimise the influence of these confounding factors such as sampling site/location. These data processing methods then allow for common patterns to be highlighted in the data, including the identification of biomarkers and determination of non-trivial associations between variables. We demonstrate the utility of this statistical workflow by jointly analysing the chemical composition and fungal biodiversity of New Zealand vineyard soils that have been managed with either organic low-input or conventional input approaches. By applying this pipeline, we were able to identify biomarkers that distinguish viticultural soil from both approaches and also unearth links and associations between the chemical and metagenomic profiles. While soil is an example of a system that can require this type of statistical methodology, there are a range of biological and ecological systems that are challenging to analyse due to the complex interplay of global and local effects. Utilising our developed pipeline will greatly enhance the way that these systems can be studied and the quality and impact of insight gained from their analysis. Complex matrices such as soil have a range of measurable characteristics, and thus data to describe them can be considered multidimensional. These characteristics can be strongly influenced by factors that introduce confounding effects that hinder analyses. Traditional statistical approaches lack the flexibility and granularity required to adequately evaluate such matrices, particularly those with large dataset of varying data types (i.e. quantitative non-compositional, quantitative compositional). We present a statistical workflow designed to effectively analyse complex, multidimensional systems, even in the presence of confounding variables. The developed methodology involves exploratory analysis to identify the presence of confounding variables, followed by data decomposition (including strategies for both compositional and non-compositional quantitative data) to minimise the influence of these confounding factors such as sampling site/location. These data processing methods then allow for common patterns to be highlighted in the data, including the identification of biomarkers and determination of non-trivial associations between variables. We demonstrate the utility of this statistical workflow by jointly analysing the chemical composition and fungal biodiversity of New Zealand vineyard soils that have been managed with either organic low-input or conventional input approaches. By applying this pipeline, we were able to identify biomarkers that distinguish viticultural soil from both approaches and also unearth links and associations between the chemical and metagenomic profiles. While soil is an example of a system that can require this type of statistical methodology, there are a range of biological and ecological systems that are challenging to analyse due to the complex interplay of global and local effects. Utilising our developed pipeline will greatly enhance the way that these systems can be studied and the quality and impact of insight gained from their analysis. [Display omitted] •Novel statistical workflow to effectively analyse complex, multidimensional systems.•Methods allow identification of biomarker and non-trivial variable associations.•Workflow demonstrated through analysing New Zealand vineyard soils.•Utility shown by jointly analysing chemical composition and fungal biodiversity.•Developed pipeline will enhance analysis of other complex multidimensional systems. Complex matrices such as soil have a range of measurable characteristics, and thus data to describe them can be considered multidimensional. These characteristics can be strongly influenced by factors that introduce confounding effects that hinder analyses. Traditional statistical approaches lack the flexibility and granularity required to adequately evaluate such matrices, particularly those with large dataset of varying data types (i.e. quantitative non-compositional, quantitative compositional). We present a statistical workflow designed to effectively analyse complex, multidimensional systems, even in the presence of confounding variables. The developed methodology involves exploratory analysis to identify the presence of confounding variables, followed by data decomposition (including strategies for both compositional and non-compositional quantitative data) to minimise the influence of these confounding factors such as sampling site/location. These data processing methods then allow for common patterns to be highlighted in the data, including the identification of biomarkers and determination of non-trivial associations between variables. We demonstrate the utility of this statistical workflow by jointly analysing the chemical composition and fungal biodiversity of New Zealand vineyard soils that have been managed with either organic low-input or conventional input approaches. By applying this pipeline, we were able to identify biomarkers that distinguish viticultural soil from both approaches and also unearth links and associations between the chemical and metagenomic profiles. While soil is an example of a system that can require this type of statistical methodology, there are a range of biological and ecological systems that are challenging to analyse due to the complex interplay of global and local effects. Utilising our developed pipeline will greatly enhance the way that these systems can be studied and the quality and impact of insight gained from their analysis.Complex matrices such as soil have a range of measurable characteristics, and thus data to describe them can be considered multidimensional. These characteristics can be strongly influenced by factors that introduce confounding effects that hinder analyses. Traditional statistical approaches lack the flexibility and granularity required to adequately evaluate such matrices, particularly those with large dataset of varying data types (i.e. quantitative non-compositional, quantitative compositional). We present a statistical workflow designed to effectively analyse complex, multidimensional systems, even in the presence of confounding variables. The developed methodology involves exploratory analysis to identify the presence of confounding variables, followed by data decomposition (including strategies for both compositional and non-compositional quantitative data) to minimise the influence of these confounding factors such as sampling site/location. These data processing methods then allow for common patterns to be highlighted in the data, including the identification of biomarkers and determination of non-trivial associations between variables. We demonstrate the utility of this statistical workflow by jointly analysing the chemical composition and fungal biodiversity of New Zealand vineyard soils that have been managed with either organic low-input or conventional input approaches. By applying this pipeline, we were able to identify biomarkers that distinguish viticultural soil from both approaches and also unearth links and associations between the chemical and metagenomic profiles. While soil is an example of a system that can require this type of statistical methodology, there are a range of biological and ecological systems that are challenging to analyse due to the complex interplay of global and local effects. Utilising our developed pipeline will greatly enhance the way that these systems can be studied and the quality and impact of insight gained from their analysis.
ArticleNumber	125954
Author	Kerner, William Fedrizzi, Bruno Pilkington, Lisa I. Franceschi, Pietro Lee, Soon A. Larcher, Roberto Bertoldi, Daniela Albanese, Davide Goddard, Matthew R.
Author_xml	– sequence: 1 givenname: Lisa I. orcidid: 0000-0002-9292-3261 surname: Pilkington fullname: Pilkington, Lisa I. email: lisa.pilkington@auckland.ac.nz organization: School of Chemical Sciences, University of Auckland, Auckland, 1010, New Zealand – sequence: 2 givenname: William surname: Kerner fullname: Kerner, William organization: School of Chemical Sciences, University of Auckland, Auckland, 1010, New Zealand – sequence: 3 givenname: Daniela orcidid: 0000-0001-7512-1286 surname: Bertoldi fullname: Bertoldi, Daniela organization: Food Characterisation and Processing Department, Technology Transfer Centre, Fondazione Edmund Mach, San Michele all’Adige, 38098, Italy – sequence: 4 givenname: Roberto orcidid: 0000-0002-4784-8389 surname: Larcher fullname: Larcher, Roberto organization: Food Characterisation and Processing Department, Technology Transfer Centre, Fondazione Edmund Mach, San Michele all’Adige, 38098, Italy – sequence: 5 givenname: Soon A. orcidid: 0000-0003-2561-4319 surname: Lee fullname: Lee, Soon A. organization: School of Biological Sciences, University of Auckland, Auckland, 1010, New Zealand – sequence: 6 givenname: Matthew R. orcidid: 0000-0002-7482-4438 surname: Goddard fullname: Goddard, Matthew R. organization: School of Biological Sciences, University of Auckland, Auckland, 1010, New Zealand – sequence: 7 givenname: Davide orcidid: 0000-0002-9493-3850 surname: Albanese fullname: Albanese, Davide organization: Unit of Computational Biology, Research and Innovation Centre, Fondazione Edmund Mach, San Michele all’Adige, 38098, Italy – sequence: 8 givenname: Pietro orcidid: 0000-0001-5711-4429 surname: Franceschi fullname: Franceschi, Pietro email: pietro.franceschi@fmach.it organization: Unit of Computational Biology, Research and Innovation Centre, Fondazione Edmund Mach, San Michele all’Adige, 38098, Italy – sequence: 9 givenname: Bruno surname: Fedrizzi fullname: Fedrizzi, Bruno email: b.fedrizzi@auckland.ac.nz organization: School of Chemical Sciences, University of Auckland, Auckland, 1010, New Zealand
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/38599113$$D View this record in MEDLINE/PubMed
BookMark	eNqFkU1v3CAQhlGUKNmk_QmtfOzFW8ZjFqMeqirqR6RUubRnRGBoWWGzBTZS_n299ebSyx4QID3PjPS-1-x8ShMx9gb4Gjhs3m_X1UQzVbPueNevoRNK9GdsBYPEFoXEc7biHFWroOdX7LqULee8Q46X7AoHoRQArtj3u6nSr2xqSFNjJtf8TjGUGuz8MfG5hNIk34z7WMMu0vJwYaSpzIKJTUkhNs5U0xSq5RW78CYWen28b9jPL59_3H5r7x--3t1-um9t34vaSiHcICQMMLiNQGGN2BB4b4xCNKi8RCJ_OHbw9OgJiBRKsCCc8APgDXu3zN3l9GdPpeoxFEtxDoTSvmgEgRvJu06cRjlKVIOSakbfHtH940hO73IYTX7WL2nNwIcFsDmVkslrG-q_6Go2IWrg-tCN3upjN_rQjV66mW3xn_2y4JT3cfFoTvQpUNbFBposuZDJVu1SODHhLyu4rEg
CitedBy_id	crossref_primary_10_1002_adma_202415160 crossref_primary_10_55959_MSU0137_0944_17_2025_80_2_114_125 crossref_primary_10_3103_S0147687425700103
Cites_doi	10.1016/j.apsoil.2005.09.007 10.1002/env.966 10.1081/CSS-120014460 10.1186/s40168-019-0758-7 10.1038/nature09944 10.1093/nar/gkl244 10.1016/j.soilbio.2015.09.002 10.1071/SR04102 10.1016/S0929-1393(00)00067-6 10.1038/s41467-020-17688-2 10.1016/0005-2795(75)90109-9 10.1016/j.isci.2021.102280 10.1007/s12571-015-0437-x 10.1038/srep09743 10.1109/34.709601 10.1371/journal.pone.0009490 10.1038/ismej.2014.210 10.1038/ismej.2015.18 10.1186/s12864-018-5160-5 10.1128/AEM.00062-07 10.1093/gigascience/giy032 10.1093/bioinformatics/bty175 10.3389/fmicb.2017.02224 10.1093/bioinformatics/bti476 10.1371/journal.pone.0152719 10.1038/s41598-019-49854-y 10.1016/S1567-1356(03)00012-6 10.1016/j.agee.2017.05.022 10.1111/1462-2920.12456 10.1146/annurev-statistics-010814-020351 10.1371/journal.pone.0160169 10.1111/j.2517-6161.1982.tb01195.x
ContentType	Journal Article
Copyright	2024 The Authors Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.
Copyright_xml	– notice: 2024 The Authors – notice: Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.
DBID	6I. AAFTH AAYXX CITATION NPM 7X8 7S9 L.6
DOI	10.1016/j.talanta.2024.125954
DatabaseName	ScienceDirect Open Access Titles Elsevier:ScienceDirect:Open Access CrossRef PubMed MEDLINE - Academic AGRICOLA AGRICOLA - Academic
DatabaseTitle	CrossRef PubMed MEDLINE - Academic AGRICOLA AGRICOLA - Academic
DatabaseTitleList	AGRICOLA PubMed MEDLINE - Academic
Database_xml	– sequence: 1 dbid: NPM name: PubMed url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: 7X8 name: MEDLINE - Academic url: https://search.proquest.com/medline sourceTypes: Aggregation Database
DeliveryMethod	fulltext_linktorsrc
Discipline	Chemistry
EISSN	1873-3573
ExternalDocumentID	38599113 10_1016_j_talanta_2024_125954 S0039914024003333
Genre	Journal Article
GeographicLocations	New Zealand
GeographicLocations_xml	– name: New Zealand
GroupedDBID	--K --M -DZ -~X .~1 0R~ 123 1B1 1RT 1~. 1~5 4.4 457 4G. 53G 5VS 6I. 7-5 71M 8P~ 9JN AABNK AACTN AAEDT AAEDW AAFTH AAHBH AAIAV AAIKJ AAKOC AALRI AAOAW AAQFI AARLI AAXUO ABJNI ABMAC ACDAQ ACGFS ACNCT ACRLP ADBBV ADECG ADEZE AEBSH AEKER AENEX AFKWA AFTJW AFZHZ AGHFR AGUBO AGYEJ AHHHB AIEXJ AIKHN AITUG AJOXV AJSZI AKRWK ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ AXJTR BKOJK BLXMC CS3 DU5 EBS EFJIC EO8 EO9 EP2 EP3 F5P FDB FIRID FLBIZ FNPLU FYGXN G-Q GBLVA IHE J1W K-O KOM M36 M41 MO0 N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. Q38 RNS ROL RPZ SCC SCH SDF SDG SDP SES SEW SPC SPCBC SSK SSZ T5K TN5 TWZ WH7 XPP YK3 YNT ZMT ~02 ~G- 29Q 3O- 9DU AAQXK AATTM AAXKI AAYJJ AAYWO AAYXX ABDPE ABEFU ABFNM ABWVN ABXDB ACLOT ACNNM ACRPL ACVFH ADCNI ADIYS ADMUD ADNMO AEIPS AEUPX AFJKZ AFPUW AGQPQ AIGII AIIUN AJQLL AKBMS AKYEP ANKPU APXCP ASPBG AVWKF AZFZN CITATION EFKBS EFLBG EJD FEDTE FGOYB HMU HVGLF HZ~ R2- SCB WUQ XOL ~HD AFXIZ AGCQF AGRNS BNPGV NPM SSH 7X8 7S9 L.6
ID	FETCH-LOGICAL-c445t-755d8571818d6535ca56e1ffaa933a39f73eef3eefc8febfe1ee9371c15d5f813
ISICitedReferencesCount	1
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001228221300001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	0039-9140 1873-3573
IngestDate	Thu Oct 02 22:49:45 EDT 2025 Wed Oct 01 17:15:57 EDT 2025 Mon Jul 21 05:55:29 EDT 2025 Sat Nov 29 05:52:26 EST 2025 Tue Nov 18 21:06:31 EST 2025 Sat Jul 06 15:30:43 EDT 2024
IsDoiOpenAccess	true
IsOpenAccess	true
IsPeerReviewed	true
IsScholarly	true
Keywords	Statistical workflow Confounding variables Soil analysis Variable association Variable transformation Compositional data
Language	English
License	This is an open access article under the CC BY license. Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.
LinkModel	OpenURL
MergedId	FETCHMERGED-LOGICAL-c445t-755d8571818d6535ca56e1ffaa933a39f73eef3eefc8febfe1ee9371c15d5f813
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ORCID	0000-0002-4784-8389 0000-0002-9292-3261 0000-0002-9493-3850 0000-0001-7512-1286 0000-0001-5711-4429 0000-0003-2561-4319 0000-0002-7482-4438
OpenAccessLink	https://dx.doi.org/10.1016/j.talanta.2024.125954
PMID	38599113
PQID	3037398979
PQPubID	23479
ParticipantIDs	proquest_miscellaneous_3153670225 proquest_miscellaneous_3037398979 pubmed_primary_38599113 crossref_citationtrail_10_1016_j_talanta_2024_125954 crossref_primary_10_1016_j_talanta_2024_125954 elsevier_sciencedirect_doi_10_1016_j_talanta_2024_125954
PublicationCentury	2000
PublicationDate	2024-07-01
PublicationDateYYYYMMDD	2024-07-01
PublicationDate_xml	– month: 07 year: 2024 text: 2024-07-01 day: 01
PublicationDecade	2020
PublicationPlace	Netherlands
PublicationPlace_xml	– name: Netherlands
PublicationTitle	Talanta (Oxford)
PublicationTitleAlternate	Talanta
PublicationYear	2024
Publisher	Elsevier B.V
Publisher_xml	– name: Elsevier B.V
References	Price, Dehal, Arkin (bib21) 2010; 5 Arumugam, Raes, Pelletier, Le Paslier (bib29) 2011; 473 Tin Kam (bib34) 1998; 20 Smilde, Jansen, Hoefsloot, Lamers, van der Greef, Timmerman (bib30) 2005; 21 Lê Cao, Ignacio Gonzalez, Dejean, with key contributors Gautier, Bartolo, contributions from Monget, Coquery, Yao, Liquet, mixOmics (bib31) 2016 Doran, Zeiss (bib2) 2000; 15 Kumar, Slud, Okrah, Hicks, Hannenhalli, Corrada Bravo (bib24) 2018; 19 Filzmoser, Hron, Reimann (bib33) 2009; 20 Kurtzman, Robnett (bib15) 2003; 3 Wang, Garrity, Tiedje, Cole (bib19) 2007; 73 Widmer, Rasche, Hartmann, Fliessbach (bib5) 2006; 33 Blakemore, Philip Lee, Daly (bib12) 1987 van Dijk (bib14) 2002; 33 Morrison-Whittle, Goddard (bib16) 2015; 9 Giraldo-Perez, Raw, Greven, Goddard (bib7) 2021; 24 Al-Busaidi, Cookson, Yamamoto (bib11) 2005; 43 DeSantis, Z, Hugenholtz, Keller, Brodie, Larsen, Piceno, Phan, Andersen (bib20) 2006; 34 Westfall, Yarkoni (bib22) 2016; 11 Matthews (bib35) 1975; 405 Taylor, Tsai, Anfang, Ross, Goddard (bib17) 2014; 6 Morrison-Whittle, Lee, Goddard (bib10) 2017; 246 Quinn, Erb, Richardson, Crowley (bib27) 2018; 34 Li (bib23) 2015; 2 Burns, Kluepfel, Strauss, Bokulich, Cantu, Steenwerth (bib4) 2015; 91 Lake (bib13) 2000 Albanese, Riccadonna, Donati, Franceschi (bib37) 2018; 7 Gloor, Macklaim, Pawlowsky-Glahn, Egozcue (bib25) 2017; 8 Lê Cao, Costello, Lakis, Bartolo, Chua, Brazeilles, Rondeau (bib32) 2016; 11 Haug, Graham, Christophersen, Lyons (bib36) 2007; 19 Albanese, Fontana, De Filippo (bib18) 2015; 5 Coller, Cestaro, Zanzotti, Bertoldi, Pindo, Larger, Albanese, Mescalchin, Donati (bib3) 2019; 7 Aitchison (bib26) 1982; 44 Hartmann, Frey, Mayer, Mäder, Widmer (bib1) 2015; 9 Harkes, Suleiman, van den Elsen, Haan, Holterman, Kuramae, Helder (bib9) 2019; 9 Guerra, Heintz-Buschart, Sikorski (bib8) 2020; 11 Pearson, Henrici (bib28) 1896; 187 Rickson, Deeks, Graves, Harris, Kibblewhite, Sakrabani (bib6) 2015; 7 Matthews (10.1016/j.talanta.2024.125954_bib35) 1975; 405 Widmer (10.1016/j.talanta.2024.125954_bib5) 2006; 33 Doran (10.1016/j.talanta.2024.125954_bib2) 2000; 15 Guerra (10.1016/j.talanta.2024.125954_bib8) 2020; 11 Rickson (10.1016/j.talanta.2024.125954_bib6) 2015; 7 van Dijk (10.1016/j.talanta.2024.125954_bib14) 2002; 33 Lê Cao (10.1016/j.talanta.2024.125954_bib31) Price (10.1016/j.talanta.2024.125954_bib21) 2010; 5 Pearson (10.1016/j.talanta.2024.125954_bib28) 1896; 187 Al-Busaidi (10.1016/j.talanta.2024.125954_bib11) 2005; 43 Kurtzman (10.1016/j.talanta.2024.125954_bib15) 2003; 3 Harkes (10.1016/j.talanta.2024.125954_bib9) 2019; 9 Morrison-Whittle (10.1016/j.talanta.2024.125954_bib10) 2017; 246 Burns (10.1016/j.talanta.2024.125954_bib4) 2015; 91 Taylor (10.1016/j.talanta.2024.125954_bib17) 2014; 6 Wang (10.1016/j.talanta.2024.125954_bib19) 2007; 73 Hartmann (10.1016/j.talanta.2024.125954_bib1) 2015; 9 Blakemore (10.1016/j.talanta.2024.125954_bib12) 1987 Lake (10.1016/j.talanta.2024.125954_bib13) 2000 Filzmoser (10.1016/j.talanta.2024.125954_bib33) 2009; 20 Smilde (10.1016/j.talanta.2024.125954_bib30) 2005; 21 Aitchison (10.1016/j.talanta.2024.125954_bib26) 1982; 44 Gloor (10.1016/j.talanta.2024.125954_bib25) 2017; 8 Morrison-Whittle (10.1016/j.talanta.2024.125954_bib16) 2015; 9 Arumugam (10.1016/j.talanta.2024.125954_bib29) 2011; 473 Coller (10.1016/j.talanta.2024.125954_bib3) 2019; 7 Li (10.1016/j.talanta.2024.125954_bib23) 2015; 2 Albanese (10.1016/j.talanta.2024.125954_bib18) 2015; 5 Kumar (10.1016/j.talanta.2024.125954_bib24) 2018; 19 Tin Kam (10.1016/j.talanta.2024.125954_bib34) 1998; 20 Haug (10.1016/j.talanta.2024.125954_bib36) 2007; 19 Westfall (10.1016/j.talanta.2024.125954_bib22) 2016; 11 Lê Cao (10.1016/j.talanta.2024.125954_bib32) 2016; 11 Albanese (10.1016/j.talanta.2024.125954_bib37) 2018; 7 DeSantis (10.1016/j.talanta.2024.125954_bib20) 2006; 34 Quinn (10.1016/j.talanta.2024.125954_bib27) 2018; 34 Giraldo-Perez (10.1016/j.talanta.2024.125954_bib7) 2021; 24
References_xml	– volume: 44 start-page: 139 year: 1982 ident: bib26 article-title: The statistical analysis of compositional data publication-title: J. R. Stat. Soc. Ser. B Methodol. – volume: 9 start-page: 1177 year: 2015 ident: bib1 article-title: Distinct soil microbial diversity under long-term organic and conventional farming publication-title: ISME J. – volume: 3 start-page: 417 year: 2003 ident: bib15 article-title: Phylogenetic relationships among yeasts of the 'Saccharomyces complex' determined from multigene sequence analyses publication-title: FEMS Yeast Res. – volume: 34 start-page: W394 year: 2006 end-page: W399 ident: bib20 article-title: NAST: a multiple sequence alignment server for comparative analysis of 16S rRNA genes publication-title: Nucleic Acids Res. – volume: 7 start-page: 1 year: 2018 ident: bib37 article-title: A practical tool for maximal information coefficient analysis publication-title: GigaScience – year: 2000 ident: bib13 article-title: Understanding Soil pH. New South Wales Acid – year: 1987 ident: bib12 article-title: Methods for Chemical Analysis of Soils; Lower Hutt, N.Z – volume: 33 start-page: 2457 year: 2002 ident: bib14 article-title: Wageningen evaluating programmes for analytical laboratories (wepal): a world of experience publication-title: Commun. Soil Sci. Plant Anal. – volume: 34 start-page: 2870 year: 2018 ident: bib27 article-title: Understanding sequencing data as compositions: an outlook and review publication-title: Bioinformatics – volume: 9 year: 2019 ident: bib9 article-title: Conventional and organic soil management as divergent drivers of resident and active fractions of major soil food web constituents publication-title: Sci. Rep. – volume: 43 start-page: 541 year: 2005 ident: bib11 article-title: Methods of pH determination in calcareous soils: use of electrolytes and suspension effect publication-title: J. Soil Res. – volume: 7 start-page: 140 year: 2019 ident: bib3 article-title: Microbiome of vineyard soils is shaped by geography and management publication-title: Microbiome – volume: 187 start-page: 253 year: 1896 ident: bib28 article-title: VII. Mathematical contributions to the theory of evolution III. Regression, heredity, and panmixia. Philosophical Transactions of the Royal Society of London. Series A publication-title: Containing Papers of a Mathematical or Physical Character – volume: 405 start-page: 442 year: 1975 ident: bib35 article-title: Comparison of the predicted and observed secondary structure of T4 phage lysozyme publication-title: Biochim. Biophys. Acta Protein Struct. – volume: 24 year: 2021 ident: bib7 article-title: A small effect of conservation agriculture on soil biodiversity that differs between biological kingdoms and geographic locations publication-title: iScience – volume: 6 start-page: 2848 year: 2014 ident: bib17 article-title: Pyrosequencing reveals regional differences in fruit-associated fungal communities publication-title: Environ. Microbiol. – volume: 11 year: 2016 ident: bib22 article-title: Statistically controlling for confounding constructs is harder than you think publication-title: PLoS One – volume: 5 start-page: 9743 year: 2015 ident: bib18 article-title: MICCA: a complete and accurate software for taxonomic profiling of metagenomic data publication-title: Sci. Rep. – volume: 11 year: 2016 ident: bib32 article-title: MixMC: a multivariate statistical framework to gain insight into microbial communities publication-title: PLoS One – volume: 20 start-page: 621 year: 2009 ident: bib33 article-title: Principal component analysis for compositional data with outliers publication-title: Environmetrics – volume: 19 start-page: 799 year: 2018 ident: bib24 article-title: Analysis and correction of compositional bias in sparse sequencing count data publication-title: BMC Genom. – volume: 11 start-page: 3870 year: 2020 ident: bib8 article-title: Blind spots in global soil biodiversity and ecosystem function research publication-title: Nat. Commun. – volume: 91 start-page: 232 year: 2015 ident: bib4 article-title: Vineyard soil bacterial diversity and composition revealed by 16S rRNA genes: differentiation by geographic features publication-title: Soil Biol. Biochem. – volume: 15 start-page: 3 year: 2000 ident: bib2 article-title: Soil health and sustainability: managing the biotic component of soil quality publication-title: Appl. Soil Ecol. – volume: 7 start-page: 351 year: 2015 ident: bib6 article-title: Input constraints to food production: the impact of soil degradation publication-title: Food Secur. – volume: 20 start-page: 832 year: 1998 ident: bib34 article-title: The random subspace method for constructing decision forests publication-title: IEEE Trans. Pattern Anal. Mach. Intell. – volume: 33 start-page: 294 year: 2006 end-page: 307 ident: bib5 article-title: Community structures and substrate utilization of bacteria in soils from organic and conventional farming systems of the DOK long-term field experiment publication-title: Appl. Soil Ecol. – volume: 9 start-page: 2003 year: 2015 ident: bib16 article-title: Quantifying the relative roles of selective and neutral processes in defining eukaryotic microbial communities publication-title: ISME J. – volume: 473 start-page: 174 year: 2011 ident: bib29 article-title: Enterotypes of the human gut microbiome publication-title: Nature – volume: 19 start-page: 209 year: 2007 ident: bib36 article-title: How to use the world's scarce selenium resources efficiently to increase the selenium concentration in food publication-title: Microb. Ecol. Health Dis. – volume: 8 start-page: 2224 year: 2017 ident: bib25 article-title: Microbiome datasets are compositional: and this is not optional publication-title: Front. Microbiol. – volume: 2 start-page: 73 year: 2015 ident: bib23 article-title: Microbiome, metagenomics, and high-dimensional compositional data analysis publication-title: Annu. Rev. Stat. Appl. – volume: 73 start-page: 5261 year: 2007 ident: bib19 article-title: Naïve bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy publication-title: Appl. Environ. Microbiol. – volume: 5 year: 2010 ident: bib21 article-title: FastTree 2 – approximately maximum-likelihood trees for large alignments publication-title: PLoS One – volume: 246 start-page: 306 year: 2017 ident: bib10 article-title: Fungal communities are differentially affected by conventional and biodynamic agricultural management approaches in vineyard ecosystems publication-title: Agric. Ecosyst. Environ. – year: 2016 ident: bib31 article-title: Omics data integration project – volume: 21 start-page: 3043 year: 2005 ident: bib30 article-title: ANOVA-simultaneous component analysis (ASCA): a new tool for analyzing designed metabolomics data publication-title: Bioinformatics – volume: 33 start-page: 294 year: 2006 ident: 10.1016/j.talanta.2024.125954_bib5 article-title: Community structures and substrate utilization of bacteria in soils from organic and conventional farming systems of the DOK long-term field experiment publication-title: Appl. Soil Ecol. doi: 10.1016/j.apsoil.2005.09.007 – volume: 20 start-page: 621 year: 2009 ident: 10.1016/j.talanta.2024.125954_bib33 article-title: Principal component analysis for compositional data with outliers publication-title: Environmetrics doi: 10.1002/env.966 – volume: 33 start-page: 2457 year: 2002 ident: 10.1016/j.talanta.2024.125954_bib14 article-title: Wageningen evaluating programmes for analytical laboratories (wepal): a world of experience publication-title: Commun. Soil Sci. Plant Anal. doi: 10.1081/CSS-120014460 – volume: 7 start-page: 140 year: 2019 ident: 10.1016/j.talanta.2024.125954_bib3 article-title: Microbiome of vineyard soils is shaped by geography and management publication-title: Microbiome doi: 10.1186/s40168-019-0758-7 – year: 1987 ident: 10.1016/j.talanta.2024.125954_bib12 – volume: 473 start-page: 174 year: 2011 ident: 10.1016/j.talanta.2024.125954_bib29 article-title: Enterotypes of the human gut microbiome publication-title: Nature doi: 10.1038/nature09944 – volume: 34 start-page: W394 year: 2006 ident: 10.1016/j.talanta.2024.125954_bib20 article-title: NAST: a multiple sequence alignment server for comparative analysis of 16S rRNA genes publication-title: Nucleic Acids Res. doi: 10.1093/nar/gkl244 – volume: 91 start-page: 232 year: 2015 ident: 10.1016/j.talanta.2024.125954_bib4 article-title: Vineyard soil bacterial diversity and composition revealed by 16S rRNA genes: differentiation by geographic features publication-title: Soil Biol. Biochem. doi: 10.1016/j.soilbio.2015.09.002 – volume: 43 start-page: 541 year: 2005 ident: 10.1016/j.talanta.2024.125954_bib11 article-title: Methods of pH determination in calcareous soils: use of electrolytes and suspension effect Aus publication-title: J. Soil Res. doi: 10.1071/SR04102 – volume: 15 start-page: 3 year: 2000 ident: 10.1016/j.talanta.2024.125954_bib2 article-title: Soil health and sustainability: managing the biotic component of soil quality publication-title: Appl. Soil Ecol. doi: 10.1016/S0929-1393(00)00067-6 – volume: 11 start-page: 3870 year: 2020 ident: 10.1016/j.talanta.2024.125954_bib8 article-title: Blind spots in global soil biodiversity and ecosystem function research publication-title: Nat. Commun. doi: 10.1038/s41467-020-17688-2 – volume: 405 start-page: 442 year: 1975 ident: 10.1016/j.talanta.2024.125954_bib35 article-title: Comparison of the predicted and observed secondary structure of T4 phage lysozyme publication-title: Biochim. Biophys. Acta Protein Struct. doi: 10.1016/0005-2795(75)90109-9 – volume: 24 year: 2021 ident: 10.1016/j.talanta.2024.125954_bib7 article-title: A small effect of conservation agriculture on soil biodiversity that differs between biological kingdoms and geographic locations publication-title: iScience doi: 10.1016/j.isci.2021.102280 – volume: 7 start-page: 351 year: 2015 ident: 10.1016/j.talanta.2024.125954_bib6 article-title: Input constraints to food production: the impact of soil degradation publication-title: Food Secur. doi: 10.1007/s12571-015-0437-x – volume: 5 start-page: 9743 year: 2015 ident: 10.1016/j.talanta.2024.125954_bib18 article-title: MICCA: a complete and accurate software for taxonomic profiling of metagenomic data publication-title: Sci. Rep. doi: 10.1038/srep09743 – volume: 19 start-page: 209 year: 2007 ident: 10.1016/j.talanta.2024.125954_bib36 article-title: How to use the world's scarce selenium resources efficiently to increase the selenium concentration in food publication-title: Microb. Ecol. Health Dis. – volume: 20 start-page: 832 year: 1998 ident: 10.1016/j.talanta.2024.125954_bib34 article-title: The random subspace method for constructing decision forests publication-title: IEEE Trans. Pattern Anal. Mach. Intell. doi: 10.1109/34.709601 – year: 2000 ident: 10.1016/j.talanta.2024.125954_bib13 – volume: 5 year: 2010 ident: 10.1016/j.talanta.2024.125954_bib21 article-title: FastTree 2 – approximately maximum-likelihood trees for large alignments publication-title: PLoS One doi: 10.1371/journal.pone.0009490 – volume: 9 start-page: 1177 year: 2015 ident: 10.1016/j.talanta.2024.125954_bib1 article-title: Distinct soil microbial diversity under long-term organic and conventional farming publication-title: ISME J. doi: 10.1038/ismej.2014.210 – ident: 10.1016/j.talanta.2024.125954_bib31 – volume: 9 start-page: 2003 year: 2015 ident: 10.1016/j.talanta.2024.125954_bib16 article-title: Quantifying the relative roles of selective and neutral processes in defining eukaryotic microbial communities publication-title: ISME J. doi: 10.1038/ismej.2015.18 – volume: 19 start-page: 799 year: 2018 ident: 10.1016/j.talanta.2024.125954_bib24 article-title: Analysis and correction of compositional bias in sparse sequencing count data publication-title: BMC Genom. doi: 10.1186/s12864-018-5160-5 – volume: 187 start-page: 253 year: 1896 ident: 10.1016/j.talanta.2024.125954_bib28 article-title: VII. Mathematical contributions to the theory of evolution III. Regression, heredity, and panmixia. Philosophical Transactions of the Royal Society of London. Series A publication-title: Containing Papers of a Mathematical or Physical Character – volume: 73 start-page: 5261 year: 2007 ident: 10.1016/j.talanta.2024.125954_bib19 article-title: Naïve bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy publication-title: Appl. Environ. Microbiol. doi: 10.1128/AEM.00062-07 – volume: 7 start-page: 1 year: 2018 ident: 10.1016/j.talanta.2024.125954_bib37 article-title: A practical tool for maximal information coefficient analysis publication-title: GigaScience doi: 10.1093/gigascience/giy032 – volume: 34 start-page: 2870 year: 2018 ident: 10.1016/j.talanta.2024.125954_bib27 article-title: Understanding sequencing data as compositions: an outlook and review publication-title: Bioinformatics doi: 10.1093/bioinformatics/bty175 – volume: 8 start-page: 2224 year: 2017 ident: 10.1016/j.talanta.2024.125954_bib25 article-title: Microbiome datasets are compositional: and this is not optional publication-title: Front. Microbiol. doi: 10.3389/fmicb.2017.02224 – volume: 21 start-page: 3043 year: 2005 ident: 10.1016/j.talanta.2024.125954_bib30 article-title: ANOVA-simultaneous component analysis (ASCA): a new tool for analyzing designed metabolomics data publication-title: Bioinformatics doi: 10.1093/bioinformatics/bti476 – volume: 11 year: 2016 ident: 10.1016/j.talanta.2024.125954_bib22 article-title: Statistically controlling for confounding constructs is harder than you think publication-title: PLoS One doi: 10.1371/journal.pone.0152719 – volume: 9 year: 2019 ident: 10.1016/j.talanta.2024.125954_bib9 article-title: Conventional and organic soil management as divergent drivers of resident and active fractions of major soil food web constituents publication-title: Sci. Rep. doi: 10.1038/s41598-019-49854-y – volume: 3 start-page: 417 year: 2003 ident: 10.1016/j.talanta.2024.125954_bib15 article-title: Phylogenetic relationships among yeasts of the 'Saccharomyces complex' determined from multigene sequence analyses publication-title: FEMS Yeast Res. doi: 10.1016/S1567-1356(03)00012-6 – volume: 246 start-page: 306 year: 2017 ident: 10.1016/j.talanta.2024.125954_bib10 article-title: Fungal communities are differentially affected by conventional and biodynamic agricultural management approaches in vineyard ecosystems publication-title: Agric. Ecosyst. Environ. doi: 10.1016/j.agee.2017.05.022 – volume: 6 start-page: 2848 year: 2014 ident: 10.1016/j.talanta.2024.125954_bib17 article-title: Pyrosequencing reveals regional differences in fruit-associated fungal communities publication-title: Environ. Microbiol. doi: 10.1111/1462-2920.12456 – volume: 2 start-page: 73 year: 2015 ident: 10.1016/j.talanta.2024.125954_bib23 article-title: Microbiome, metagenomics, and high-dimensional compositional data analysis publication-title: Annu. Rev. Stat. Appl. doi: 10.1146/annurev-statistics-010814-020351 – volume: 11 year: 2016 ident: 10.1016/j.talanta.2024.125954_bib32 article-title: MixMC: a multivariate statistical framework to gain insight into microbial communities publication-title: PLoS One doi: 10.1371/journal.pone.0160169 – volume: 44 start-page: 139 year: 1982 ident: 10.1016/j.talanta.2024.125954_bib26 article-title: The statistical analysis of compositional data publication-title: J. R. Stat. Soc. Ser. B Methodol. doi: 10.1111/j.2517-6161.1982.tb01195.x
SSID	ssj0002303
Score	2.4445453
Snippet	Complex matrices such as soil have a range of measurable characteristics, and thus data to describe them can be considered multidimensional. These...
SourceID	proquest pubmed crossref elsevier
SourceType	Aggregation Database Index Database Enrichment Source Publisher
StartPage	125954
SubjectTerms	biodiversity biomarkers chemical composition Compositional data Confounding variables data collection fungi metagenomics New Zealand soil Soil analysis Statistical workflow Variable association Variable transformation vineyards viticulture
Title	Integration and holistic analysis of multiple multidimensional soil data sets
URI	https://dx.doi.org/10.1016/j.talanta.2024.125954 https://www.ncbi.nlm.nih.gov/pubmed/38599113 https://www.proquest.com/docview/3037398979 https://www.proquest.com/docview/3153670225
Volume	274
WOSCitedRecordID	wos001228221300001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVESC databaseName: Elsevier SD Freedom Collection Journals 2021 customDbUrl: eissn: 1873-3573 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0002303 issn: 0039-9140 databaseCode: AIEXJ dateStart: 19950101 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV3db9MwELdYhwQviG_Kx2QkxEuVssRxbT9OUycGpewhk_pmuYktdVRJ13RT_3zOsZ1UaGPjgYdGqRWnie_X8935_DuEPhWCUJPSJMph-rHRqsNIKFCGiilVUJ4nh6ahzJ-w6ZTPZuLM5-nWTTkBVpZ8uxWr_ypqaANh262z_yDu9qbQAOcgdDiC2OF4L8GfegKIkGcM6q0hY4YvHf9Im0fYnBSW4t_RcwzqarEc2LzRQa0dy1OwXTObBQntlqB063Li2yjC2WL5q8vFnyxq1YVjv-u131XjgzttCECvN3bxq9vq3s4Rk4ZjZCf3u9oNTyRpm8raqlwiQKM6TqagcsEVHqyGYFsJmkY3KnIXU7iwNJD21Yb21r5DN3OF1frpT3lyPpnIbDzLPq8uI1tTzK69-wIre2g_YVTwHto_Oh3PvrUzNbhfnpTZPWK3w-vLjb98m-1ym2_S2CjZU_TEOxf4yIHiGXqgy-fo0XGo6fcC_dgBBwZw4AAOHMCBK4MDOPCf4MAWHNiCA1twvETnJ-Ps-GvkC2pEeZrSTcQoLTgFayTmxYgSmis60rExSglCFBGGEa2N_eTc6LnRsdaWLzGPaUENj8kr1CurUr9BeERjlccFjzUodFaQuWFCjUxaCEOTeZz0URqGSuaebd4WPVnKkFZ4If0ISzvC0o1wHw3bbitHt3JXBx7kIL3N6GxBCUi6q-vHIDcJYrALZarU1VUtARaMCC6Y-Ms1YCqMGFjAtI9eO6G3T0w4BbcrJm_v0fsdetz9bd6j3mZ9pT-gh_n1ZlGvD9Aem_EDj9vf39uwSg
linkProvider	Elsevier
openUrl	ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Integration+and+holistic+analysis+of+multiple+multidimensional+soil+data+sets&rft.jtitle=Talanta+%28Oxford%29&rft.au=Pilkington%2C+Lisa+I&rft.au=Kerner%2C+William&rft.au=Bertoldi%2C+Daniela&rft.au=Larcher%2C+Roberto&rft.date=2024-07-01&rft.issn=0039-9140&rft.volume=274+p.125954-&rft_id=info:doi/10.1016%2Fj.talanta.2024.125954&rft.externalDBID=NO_FULL_TEXT
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0039-9140&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0039-9140&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0039-9140&client=summon