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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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| Publicado no: | BMC Bioinformatics |
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| Autor principal: | |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
BioMed Central
2015
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| Assuntos: | |
| Acesso em linha: | 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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