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Points of significance

Comparing samples—part II

Nature Methods volume 11, pages 355–356 (2014)Cite this article

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When a large number of tests are performed, P values must be interpreted differently.

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Figure 1: The experimental design of our gene expression simulation.
Figure 2: Family-wise error rate (FWER) methods such as Bonferroni's negatively affect statistical power in comparisons across many tests.
Figure 3: The shape of the distribution of unadjusted P values can be used to infer the fraction of hypotheses that are null and the false discovery rate (FDR).

References

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Authors and Affiliations

  1. Martin Krzywinski is a staff scientist at Canada's Michael Smith Genome Sciences Centre.,

    Martin Krzywinski

  2. Naomi Altman is a Professor of Statistics at The Pennsylvania State University.,

    Naomi Altman

Authors
  1. Martin Krzywinski
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  2. Naomi Altman
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The authors declare no competing financial interests.

Supplementary information

Supplementary Table 1

Table can be used to explore comparisons across many tests. (ZIP 188 kb)

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Krzywinski, M., Altman, N. Comparing samples—part II. Nat Methods 11, 355–356 (2014). https://doi.org/10.1038/nmeth.2900

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