Difference between revisions of "Rank Product analysis"
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=Rank products: a simple, yet powerful, new method to detect differentially regulated genes in replicated microarray experiments= | =Rank products: a simple, yet powerful, new method to detect differentially regulated genes in replicated microarray experiments= | ||
| − | ''Rainer Breitling, Patrick | + | ''Rainer Breitling, Patrick Armengaud, Anna Amtmanna, Pawel Herzykb'' |
==Overview== | ==Overview== | ||
| − | + | Rank Product is a non parametric statistical method of analysing microarray data. It assumes that under the null hypothesis, the order of all items is random, and the probability of findng a specific item among the top ''r'' of ''n'' items in a list is ''p = r/n''. | |
| + | |||
| + | Multiplying theses probabilities over i replicates leads to the rank product definition; | ||
| + | |||
| + | <math>\prod_i \over{r_i}{n_i}</math> | ||
| + | |||
| + | where r<sub>i</sub> is the rank of the item in the i-th list and n<sub>i</sub> is the total number of items in the i-th list. | ||
=See also= | =See also= | ||
*[http://www.brc.dcs.gla.ac.uk/~rb106x/publications/RankProducts_FEBS.pdf Publication] | *[http://www.brc.dcs.gla.ac.uk/~rb106x/publications/RankProducts_FEBS.pdf Publication] | ||
*[http://www.bioconductor.org/packages/1.9/bioc/html/RankProd.html rankProd BioC package] | *[http://www.bioconductor.org/packages/1.9/bioc/html/RankProd.html rankProd BioC package] | ||
| + | *[http://www.bioconductor.org/packages/1.9/bioc/vignettes/RankProd/inst/doc/RankProd.pdf rankProd documentation] | ||
Revision as of 21:10, 5 March 2007
Rank products: a simple, yet powerful, new method to detect differentially regulated genes in replicated microarray experiments
Rainer Breitling, Patrick Armengaud, Anna Amtmanna, Pawel Herzykb
Overview
Rank Product is a non parametric statistical method of analysing microarray data. It assumes that under the null hypothesis, the order of all items is random, and the probability of findng a specific item among the top r of n items in a list is p = r/n.
Multiplying theses probabilities over i replicates leads to the rank product definition;
[math]\prod_i \over{r_i}{n_i}[/math]
where ri is the rank of the item in the i-th list and ni is the total number of items in the i-th list.
