Mercurial > repos > marie-tremblay-metatoul > asca
diff ssq.R @ 0:93312041f1d5 draft default tip
planemo upload for repository https://github.com/workflow4metabolomics/ascaw4m commit 7ea9b0f8abc5a60c2c04fd2098788497f14766b6
author | marie-tremblay-metatoul |
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date | Fri, 21 Sep 2018 05:51:14 -0400 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/ssq.R Fri Sep 21 05:51:14 2018 -0400 @@ -0,0 +1,58 @@ +library(lmdme) +library(MetStaT) + +## Data : attention standardiser au prealable +data <- read.table("E:/PROJETS/Asca_W4M/Test_Matlab_data.txt", sep="\t", dec=",", header=TRUE, row.names=1) +design <- read.table("E:/PROJETS/Asca_W4M/Test_Matlab_design.txt", sep="\t", dec=",", header=TRUE) +design[,1] <- as.factor(design[,1]) +design[,2] <- as.factor(design[,2]) + +## Verifier noms + + +fit <- lmdme(model=~F1 + F2 + F1:F2, data=data, design=design) + +permuted <- permutation(model=~F1*F2, data=data, design=design, NPermutations=100, nCpus=3) + +decomposition(fit, decomposition = "pca", scale="none", type="coefficient") + + + + +ssq <- function(fit) +{ + Overall_means <- sum(sum(fitted.values(fit)$'(Intercept)'^2))/sum(sum(data^2)) + Factors <- c(sum(sum(fitted.values(fit)$'F1'^2))/sum(sum(data^2)), sum(sum(fitted.values(fit)$'F2'^2))/sum(sum(data^2))) + Interactions <- sum(sum(fitted.values(fit)$'F1:F2'^2))/sum(sum(data^2)) + Residuals <- 1 - Overall_means - Factors[1] - Factors[2] - Interactions + + return(list(Overall_means, Factors, Interactions, Residuals)) +} + + +par(mfrow=c(2,2)) +biplot(fit, xlabs="o", mfcol=NULL) +##Just the term of interest +biplot(fit, xlabs="o", term="F1") +##In separate graphics +biplot(fit, xlabs="o", term=c("F1", "F2"), mfcol=c(1,1)) +##All terms in the same graphic +biplot(fit, xlabs="o", mfcol=c(1,3)) + +test <-lapply(permuted, FUN = ssq) +test1 <- matrix(unlist(test), ncol=5, byrow=TRUE) +test[2:101] + +apply(apply(test1, 2, FUN = function(x){x > x[1]})[-1,], 2 , sum) / (length(test)-1) + +score_moyen <- data.frame(fit@components$F1$rotation) + +score <- data.frame(cbind(design, t(fit@residuals$'F1:F2')%*%fit@components$F1$rotation)) + +pc <- fit@components$F1$sdev / sum(fit@components$F1$sdev) + +sp <- ggplot(score_moyen, aes(x=PC1, y=PC2)) +sp + geom_point(size=2) + xlab(paste("PC1", round(pc[1]*100,1), "%")) + ylab(paste("PC2", round(pc[2]*100,1), "%")) + + geom_text(data=score, aes(PC1, PC2, label=Ind, col=F1), size=4, hjust=0, nudge_x=0.05, vjust=0, nudge_y=0.5) + +