search for: rawp2adjp

Hello R experts, I am trying to analyze this dataset and am stuck on this problem for quite some time now. I am using mt.rawp2adjp. the output that came out was a matrix with two colums since I had asked it to calculate the adjusted p values using one method. so it has the two columns as: rawp BH I combined these using cbind with my actual dataframe. checked using head all was fine. thereafter I am trying to extract the rows...

Hola a todos, Tengo un pequeño problemilla... Tengo unas 9000 variables que he contrastado con 1 en concreto con el test de wilcoxon. He calculado el p-valor, y queria corregirlo con el permutation-based FDR. He encontrado una funcion con R comp.fdr()que hace esta corrección, pero te pide que le pongas las variables con las observaciones y te hace el test (según he entendido). Yo solo quiero

> dim(data.sub) [1] 10000 140 #####extracting all differentially express genes########## library(multtest) two_side<- (1-pt(abs(data.sub),50))*2 diff<- mt.rawp2adjp(two_side) all_differ<-diff[[1]][37211:10000,] all_differ #####list of differentially expressed genes########## > probe.names<- + all_differ[[2]][all_differ[[1]][,"BY"]<=0.01] Error in all_differ[[1]][, "BY"] : incorrect number of dimensions Hi, I am pretty new wi...

...bilities of association for terms in the GeneOntology database. I have ~4e7 probabilities and I would like to correct for multiple testing. At the moment I have something like the following: pv is a vector containing my 4e7 probabilities. To run the multiple testing corrections I do: mt <- mt.rawp2adjp(pv, proc="BH") Because of the size of the vector this takes a VERY long time and a LOT of memory. I cannot split the job into smaller ones since all values in the vector are required for the calculation. Can anyone think of a trick that would allow me to reduce the memory usage of this...

...---- snip multtest Multiple Testing Procedures 1.3.3 ----------snip Function Description golub Gene expression dataset from Golub et al. (1999) mt.maxT Step-down maxT and minP multiple testing procedures mt.plot Plotting results from multiple testing procedures mt.rawp2adjp Adjusted p-values for simple multiple testing procedures mt.reject Identity and number of rejected hypotheses mt.sample.teststat Permutation distribution of test statistics and raw (unadjusted) p-values mt.teststat Computing test statistics for each row of a data frame -...

...ions, I should correct this output by the total number of possible tests conducted (3121): >phyper(26,830,31042,337, lower.tail=F)*3121 >phyper(16,387,31042,337, lower.tail=F)*3121 But I would like to perform FDR, i.e. Benjamini correction. I know that multtest package has the function mt.rawp2adjp() but I would need to save all the p.values for the 3121 in a vector and use this as a parameter of the function. Is there another way of computing this adjusted p.value for only some of the categories? Thanks for your help, David (R version 2.6.0) (Windows OS)

...pat,sum(CLASSE!=""),para$classe[1],para$classe[2]), sep="\t",quote=F,row.names=F, col.names=names(Resultats)) } if (.method != 1) { procs<-c("Bonferroni","BH") [.method-1] adj1<-mt.rawp2adjp(Resultats[,2],procs) Resultats[,2] <- adj1[[1]][,2][order(adj1$index)] adj2<-mt.rawp2adjp(Resultats[,3],procs) Resultats[,3] <- adj2[[1]][,2][order(adj2$index)] adj3<-mt.rawp2adjp(Resultats[,4],procs) Resultats[,4] <- adj3[[1]][,2][or...

...---- snip multtest Multiple Testing Procedures 1.3.3 ----------snip Function Description golub Gene expression dataset from Golub et al. (1999) mt.maxT Step-down maxT and minP multiple testing procedures mt.plot Plotting results from multiple testing procedures mt.rawp2adjp Adjusted p-values for simple multiple testing procedures mt.reject Identity and number of rejected hypotheses mt.sample.teststat Permutation distribution of test statistics and raw (unadjusted) p-values mt.teststat Computing test statistics for each row of a data frame -...