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Principal component analysis for designed experiments
BACKGROUND: Principal component analysis is used to summarize matrix data, such as found in transcriptome, proteome or metabolome and medical examinations, into fewer dimensions by fitting the matrix to orthogonal axes. Although this methodology is frequently used in multivariate analyses, it has di...
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| Wydane w: | BMC Bioinformatics |
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| 1. autor: | |
| Format: | Artigo |
| Język: | Inglês |
| Wydane: |
BioMed Central
2015
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| Hasła przedmiotowe: | |
| Dostęp online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4682404/ https://ncbi.nlm.nih.gov/pubmed/26678818 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1471-2105-16-S18-S7 |
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