Hi, just wondering how the the interaction terms can be handled as "controls" here. Any way to add them rather than manually create new 'interaction variables' in the data? Cheers.

• https://github.com/kevinblighe/RegParallel https://bioconductor.org/packages/release/data/experiment/vignettes/RegParallel/inst/doc/RegParallel.html
• https://pubmed.ncbi.nlm.nih.gov/25769333/

install.packages("ezcox")#先安装包 packageVersion("ezcox")#0.4.0版本 library(survival) library(ezcox) library("devtools") install.packages("devtools") devtools::install_github("ShixiangWang/ezcox") lung$ph.ecog <- factor(lung$ph.ecog) zz <- ezcox(lung, covariates = c("sex", "ph.ecog"), controls = "age", return_models = TRUE) zz mds <- get_models(zz) str(mds, max.level = 1) install.packages("forestmodel") library("forestmodel") show_models(mds) 问题是没有show-models这个函数

library(survival)
### write a function
fastcox_single <- function(num){
  data= cbind(clin,expreset[,num])
  UniNames <- colnames(data)[-c(1:2)]
  do.call(rbind,lapply(UniNames,function(i){
    surv =as.formula(paste('Surv(times, status)~',i))
    cur_cox=coxph(surv, data = data)
    x = summary(cur_cox)
    HR=x$coefficients[i,"exp(coef)"]
    HR.confint.lower = signif(x$conf.int[i,"lower .95"],3)
    HR.confint.upper = signif(x$conf.int[i,"upper .95"],3)
    CI <- paste0("(",HR.confint.lower, "-",HR.confint.upper,")")
    p.value=x$coef[i,"Pr(>|z|)"]
    data.frame(gene=i,HR=HR,CI=CI,p.value=p.value)
  }))
}


clin = share.data[,1:2]
expreset = share.data[,-c(1:2)]
length = ncol(expreset)
groupdf = data.frame(colnuber = seq(1,length),
                     group = rep(1:ceiling(length/100),each=100,length.out=length))
index = split(groupdf$colnuber,groupdf$group)
library(future.apply)
# options(future.globals.maxSize= 891289600)
plan(multiprocess)
share.data.os.result=do.call(rbind,future_lapply(index,fastcox_single))


#=== Use ezcox
# devtools::install_github("ShixiangWang/ezcox")
res = ezcox::ezcox(share.data, covariates = colnames(share.data)[-(1:2)], parallel = TRUE, time = "times")


share.data$VIM.INHBE
tt = ezcox::ezcox(share.data, covariates = "VIM.INHBE", return_models = T, time = "times")

大批量计算时两者时间差4倍

诗翔：

我用你的这个R包，有两个建议，你可以改进一下：

1. 对covariates的顺序，按照用户给的顺序进行展示，现在是按照字符的大小排序的。
2. 对HR太大的值，使用科学记数法进行展示

这个是用的代码

zz = ezcox(
  scores.combined,
  covariates = c("JSI", "Tindex", "Subclonal_Aca", "Subclonal_Nec", "ITH_Aca", "ITH_Nec"),
  controls = "Age",
  time = "Survival_months",
  status = "Death",
  return_models = TRUE
)

mds = get_models(zz)

show_models(mds, drop_controls = TRUE)

这个是现在的图

See

library(survival)
library(forestmodel)
library(ezcox)
show_forest(lung, covariates = c("sex", "ph.ecog"), controls = "age", format_options = forest_model_format_options(text_size = 3))

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