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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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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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BioMed Central
2015
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4682404/ https://www.ncbi.nlm.nih.gov/pubmed/26678818 http://dx.doi.org/10.1186/1471-2105-16-S18-S7 |