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Genome-wide Protein-protein Interaction Screening by Protein-fragment Complementation Assay PCA in Living Cells
Published on: March 3, 2015
Iain M Johnstone1, Debashis Paul2
1Department of Statistics, Stanford University, Stanford CA 94305.
High-dimensional data can cause issues with principal component analysis (PCA). This study explores eigenvalue bias and eigenvector inconsistency in PCA, offering new methods for covariance matrix estimation.
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