DLBCL {maxstat} | R Documentation |
A data frame with gene expression data from DLBCL (diffuse large B-cell lymphoma) patients.
data("DLBCL")
DLCLid
DLBCL identifier
GEG
Gene Expression Group
time
survival time in month
cens
censoring: 0 cencored, 1 dead
IPI
International Prognostic Index
MGE
Mean Gene Expression
Except of MGE
, the data is published at
http://llmpp.nih.gov/lymphoma/data.shtml. MGE
is the mean of
the gene expression.
Ash A. Alizadeh et. al (2000), Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature, 403, 504–509
library("survival") set.seed(29) # compute the cutpoint and plot the empirical process mod <- maxstat.test(Surv(time, cens) ~ MGE, data=DLBCL, smethod="LogRank") print(mod) ## Not run: # postscript("statDLBCL.ps", horizontal=F, width=8, height=8) pdf("statDLBCL.pdf", width=8, height=8) ## End(Not run) par(mai=c(1.0196235, 1.0196235, 0.8196973, 0.4198450)) plot(mod, cex.lab=1.6, cex.axis=1.6, xlab="Mean gene expression",lwd=2) ## Not run: dev.off() ## End(Not run) # significance of the cutpoint # limiting distribution maxstat.test(Surv(time, cens) ~ MGE, data=DLBCL, smethod="LogRank", pmethod="Lau92", iscores=TRUE) # improved Bonferroni inequality, plot with significance bound maxstat.test(Surv(time, cens) ~ MGE, data=DLBCL, smethod="LogRank", pmethod="Lau94", iscores=TRUE) mod <- maxstat.test(Surv(time, cens) ~ MGE, data=DLBCL, smethod="LogRank", pmethod="Lau94", alpha=0.05) plot(mod, xlab="Mean gene expression") ## Not run: # postscript(file="RNewsStat.ps",horizontal=F, width=8, height=8) pdf("RNewsStat.pdf", width=8, height=8) ## End(Not run) par(mai=c(1.0196235, 1.0196235, 0.8196973, 0.4198450)) plot(mod, xlab="Mean gene expression", cex.lab=1.6, cex.axis=1.6) ## Not run: dev.off() ## End(Not run) # small sample solution Hothorn & Lausen maxstat.test(Surv(time, cens) ~ MGE, data=DLBCL, smethod="LogRank", pmethod="HL") # normal approximation maxstat.test(Surv(time, cens) ~ MGE, data=DLBCL, smethod="LogRank", pmethod="exactGauss", iscores=TRUE, abseps=0.01) # conditional Monte-Carlo maxstat.test(Surv(time, cens) ~ MGE, data=DLBCL, smethod="LogRank", pmethod="condMC", B = 9999) # survival analysis and plotting like in Alizadeh et al. (2000) splitGEG <- rep(1, nrow(DLBCL)) DLBCL <- cbind(DLBCL, splitGEG) DLBCL$splitGEG[DLBCL$GEG == "Activated B-like"] <- 0 plot(survfit(Surv(time, cens) ~ splitGEG, data=DLBCL), xlab="Survival time in month", ylab="Probability") text(90, 0.7, "GC B-like") text(60, 0.3, "Activated B-like") splitIPI <- rep(1, nrow(DLBCL)) DLBCL <- cbind(DLBCL, splitIPI) DLBCL$splitIPI[DLBCL$IPI <= 2] <- 0 plot(survfit(Surv(time, cens) ~ splitIPI, data=DLBCL), xlab="Survival time in month", ylab="Probability") text(90, 0.7, "Low clinical risk") text(60, 0.25, "High clinical risk") # survival analysis using the cutpoint splitMGE <- rep(1, nrow(DLBCL)) DLBCL <- cbind(DLBCL, splitMGE) DLBCL$splitMGE[DLBCL$MGE <= mod$estimate] <- 0 ## Not run: # postscript("survDLBCL.ps",horizontal=F, width=8, height=8) pdf("survDLBCL.pdf", width=8, height=8) ## End(Not run) par(mai=c(1.0196235, 1.0196235, 0.8196973, 0.4198450)) plot(survfit(Surv(time, cens) ~ splitMGE, data=DLBCL), xlab = "Survival time in month", ylab="Probability", cex.lab=1.6, cex.axis=1.6, lwd=2) text(90, 0.9, expression("Mean gene expression" > 0.186), cex=1.6) text(90, 0.45, expression("Mean gene expression" <= 0.186 ), cex=1.6) ## Not run: dev.off() ## End(Not run)