Principal component analysis (original) (raw)

Points of Significance

Nature Methods volume 14, pages 641–642 (2017)Cite this article

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PCA helps you interpret your data, but it will not always find the important patterns.

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References

  1. Altman, N. & Krzywinski, M. Nat. Methods 14, 545–546 (2017).
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Authors and Affiliations

  1. PhD candidate at Canada's Michael Smith Genome Sciences Centre,
    Jake Lever
  2. staff scientist at Canada's Michael Smith Genome Sciences Centre,
    Martin Krzywinski
  3. Professor of Statistics at The Pennsylvania State University,
    Naomi Altman

Authors

  1. Jake Lever
  2. Martin Krzywinski
  3. Naomi Altman

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The authors declare no competing financial interests.

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Lever, J., Krzywinski, M. & Altman, N. Principal component analysis.Nat Methods 14, 641–642 (2017). https://doi.org/10.1038/nmeth.4346

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