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Strategy for minimi...
Strategy for minimizing between-study variation of large-scale phenotypic experiments using multivariate analysis
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- Pinto, Rui Climaco, 1972- (författare)
- Umeå universitet,Kemiska institutionen,Computational Life Science Cluster (CLiC)
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- Gerber, Lorenz (författare)
- Swedish University of Agricultural Sciences,Sveriges lantbruksuniversitet,Umeå universitet,Umeå Plant Science Centre (UPSC),Department of Forest Genetics and Plant Physiology,Institutionen för skoglig genetik och växtfysiologi
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- Eliasson, Mattias (författare)
- Umeå universitet,Kemiska institutionen,Computational Life Science Cluster (CLiC)
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- Sundberg, Björn (författare)
- Swedish University of Agricultural Sciences,Sveriges lantbruksuniversitet,Umeå universitet,Umeå Plant Science Centre (UPSC),Department of Forest Genetics and Plant Physiology,Institutionen för skoglig genetik och växtfysiologi
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- Trygg, Johan (författare)
- Umeå universitet,Kemiska institutionen,Computational Life Science Cluster (CLiC)
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(creator_code:org_t)
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- 2012-10-01
- 2012
- Engelska.
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Ingår i: Analytical Chemistry. - : American Chemical Society (ACS). - 0003-2700 .- 1520-6882. ; 84:20, s. 8675-8681
- Relaterad länk:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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https://res.slu.se/i...
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Abstract
Ämnesord
Stäng
- We have developed a multistep strategy that integrates data from several large-scale experiments that suffer from systematic between-experiment variation. This strategy removes such variation that would otherwise mask differences of interest. It was applied to the evaluation of wood chemical analysis of 736 hybrid aspen trees: wild-type controls and transgenic trees potentially involved in wood formation. The trees were grown in four different greenhouse experiments imposing significant variation between experiments. Pyrolysis coupled to gas chromatography/mass spectrometry (Py-GC/MS) was used as a high throughput-screening platform for fingerprinting of wood chemotype. Our proposed strategy includes quality control, outlier detection, gene specific classification, and consensus analysis. The orthogonal projections to latent structures discriminant analysis (OPLS-DA) method was used to generate the consensus chemotype profiles for each transgenic line. These were thereafter compiled to generate a global dataset. Multivariate analysis and cluster analysis techniques revealed a drastic reduction in between-experiment variation that enabled a global analysis of all transgenic lines from the four independent experiments. Information from in-depth analysis of specific transgenic lines and independent peak identification validated our proposed strategy.
Ämnesord
- NATURVETENSKAP -- Kemi -- Analytisk kemi (hsv//swe)
- NATURAL SCIENCES -- Chemical Sciences -- Analytical Chemistry (hsv//eng)
Nyckelord
- Phenotypic profiling
- functional genomics
- OPLS-DA
- multivariate
- Py-GC-MS
- data integration
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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