Difference between revisions of "Statistics"
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| − | Normal | + | =False Discovery Rate= |
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| + | False discovery rate control is a procedure that is less stringent than a classical Bonferroni correction. | ||
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| + | ==Benjamini–Hochberg Controll Procedure== | ||
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| + | Rank the ''p''-values from smallest to largest. Begin at 1, and increase the rank: 1, 2, 3, 4, 5, ... the rank is ''k''. | ||
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| + | Choose a false discovery rate ''q'', for example ''q''=0.1. | ||
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| + | The total number of independent tests is ''m''. If the level of gene expression for 20,000 genes is measured and tested then ''m''=20,000. | ||
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| + | Accept the tests with ''p''-values lower than ''qk''/''m''. | ||
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| + | You estimate that a fraction ''q'' of these tests are false positives, due to random chance, but that the remaining ones are true positives. | ||
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| + | Benjamini, Y., Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. ''Journal of the Royal Statistical Society, Series B''. 57 (1): 289–300. | ||
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| + | =Normal Distribution= | ||
https://www.maa.org/sites/default/files/pdf/upload_library/22/Allendoerfer/stahl96.pdf | https://www.maa.org/sites/default/files/pdf/upload_library/22/Allendoerfer/stahl96.pdf | ||
Revision as of 07:31, 13 August 2018
False Discovery Rate
False discovery rate control is a procedure that is less stringent than a classical Bonferroni correction.
Benjamini–Hochberg Controll Procedure
Rank the p-values from smallest to largest. Begin at 1, and increase the rank: 1, 2, 3, 4, 5, ... the rank is k.
Choose a false discovery rate q, for example q=0.1.
The total number of independent tests is m. If the level of gene expression for 20,000 genes is measured and tested then m=20,000.
Accept the tests with p-values lower than qk/m.
You estimate that a fraction q of these tests are false positives, due to random chance, but that the remaining ones are true positives.
Benjamini, Y., Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society, Series B. 57 (1): 289–300.
Normal Distribution
https://www.maa.org/sites/default/files/pdf/upload_library/22/Allendoerfer/stahl96.pdf
https://www.embedded.com/print/4413095
Derivation of the normal distribution from the binomial:
http://www.m-hikari.com/imf/imf-2017/9-12-2017/p/baguiIMF9-12-2017.pdf
