Last updated: 2023-04-18

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Unstaged changes:
    Modified:   analysis/DEG-GO_analysis.Rmd
    Modified:   analysis/run_all_analysis.Rmd
    Modified:   code/Cormotifgenelist.R
    Modified:   code/eQTLcodes.R

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File Version Author Date Message
Rmd 6f6aaf4 reneeisnowhere 2023-04-18 new Cormotif analysis with codes
html d0f459b reneeisnowhere 2023-04-18 Build site.
Rmd 67b2a09 reneeisnowhere 2023-04-18 new Cormotif analysis with codes
Rmd a64bbe1 reneeisnowhere 2023-04-18 updated with new cormotif method
html 9e37491 reneeisnowhere 2023-04-16 Build site.
Rmd 6d925a2 reneeisnowhere 2023-04-16 updating cormotif with updated RNAseq counts
Rmd 4e52216 reneeisnowhere 2023-03-31 End of week updates
Rmd c365253 reneeisnowhere 2023-03-22 updated code and plots
Rmd 3a26d52 reneeisnowhere 2023-03-22 Wed poster analysis changes
Rmd a150323 reneeisnowhere 2023-03-20 addingcormotif analysis and go on DEGs

library(tidyverse)
library(gprofiler2)
library(readr)
library(BiocGenerics)
library(gridExtra)
library(VennDiagram)
library(kableExtra)
library(scales)
library(ggVennDiagram)
library(Cormotif)
library(RColorBrewer)

Creation of the data set:

## Fit limma model using code as it is found in the original cormotif code. It has
## only been modified to add names to the matrix of t values, as well as the
## limma fits

limmafit.default <- function(exprs,groupid,compid) {
  limmafits  <- list()
  compnum    <- nrow(compid)
  genenum    <- nrow(exprs)
  limmat     <- matrix(0,genenum,compnum)
  limmas2    <- rep(0,compnum)
  limmadf    <- rep(0,compnum)
  limmav0    <- rep(0,compnum)
  limmag1num <- rep(0,compnum)
  limmag2num <- rep(0,compnum)

  rownames(limmat)  <- rownames(exprs)
  colnames(limmat)  <- rownames(compid)
  names(limmas2)    <- rownames(compid)
  names(limmadf)    <- rownames(compid)
  names(limmav0)    <- rownames(compid)
  names(limmag1num) <- rownames(compid)
  names(limmag2num) <- rownames(compid)

  for(i in 1:compnum) {
    selid1 <- which(groupid == compid[i,1])
    selid2 <- which(groupid == compid[i,2])
    eset   <- new("ExpressionSet", exprs=cbind(exprs[,selid1],exprs[,selid2]))
    g1num  <- length(selid1)
    g2num  <- length(selid2)
    designmat <- cbind(base=rep(1,(g1num+g2num)), delta=c(rep(0,g1num),rep(1,g2num)))
    fit <- lmFit(eset,designmat)
    fit <- eBayes(fit)
    limmat[,i] <- fit$t[,2]
    limmas2[i] <- fit$s2.prior
    limmadf[i] <- fit$df.prior
    limmav0[i] <- fit$var.prior[2]
    limmag1num[i] <- g1num
    limmag2num[i] <- g2num
    limmafits[[i]] <- fit

    # log odds
    # w<-sqrt(1+fit$var.prior[2]/(1/g1num+1/g2num))
    # log(0.99)+dt(fit$t[1,2],g1num+g2num-2+fit$df.prior,log=TRUE)-log(0.01)-dt(fit$t[1,2]/w, g1num+g2num-2+fit$df.prior, log=TRUE)+log(w)
  }
  names(limmafits) <- rownames(compid)
  limmacompnum<-nrow(compid)
  result<-list(t       = limmat,
               v0      = limmav0,
               df0     = limmadf,
               s20     = limmas2,
               g1num   = limmag1num,
               g2num   = limmag2num,
               compnum = limmacompnum,
               fits    = limmafits)
}

limmafit.counts <-
  function (exprs, groupid, compid, norm.factor.method = "TMM", voom.normalize.method = "none")
  {
    limmafits  <- list()
    compnum    <- nrow(compid)
    genenum    <- nrow(exprs)
    limmat     <- matrix(NA,genenum,compnum)
    limmas2    <- rep(0,compnum)
    limmadf    <- rep(0,compnum)
    limmav0    <- rep(0,compnum)
    limmag1num <- rep(0,compnum)
    limmag2num <- rep(0,compnum)

    rownames(limmat)  <- rownames(exprs)
    colnames(limmat)  <- rownames(compid)
    names(limmas2)    <- rownames(compid)
    names(limmadf)    <- rownames(compid)
    names(limmav0)    <- rownames(compid)
    names(limmag1num) <- rownames(compid)
    names(limmag2num) <- rownames(compid)

    for (i in 1:compnum) {
      message(paste("Running limma for comparision",i,"/",compnum))
      selid1 <- which(groupid == compid[i, 1])
      selid2 <- which(groupid == compid[i, 2])
      # make a new count data frame
      counts <- cbind(exprs[, selid1], exprs[, selid2])

      # remove NAs
      not.nas <- which(apply(counts, 1, function(x) !any(is.na(x))) == TRUE)

      # runn voom/limma
      d <- DGEList(counts[not.nas,])
      d <- calcNormFactors(d, method = norm.factor.method)
      g1num <- length(selid1)
      g2num <- length(selid2)
      designmat <- cbind(base = rep(1, (g1num + g2num)), delta = c(rep(0,
                                                                       g1num), rep(1, g2num)))

      y <- voom(d, designmat, normalize.method = voom.normalize.method)
      fit <- lmFit(y, designmat)
      fit <- eBayes(fit)

      limmafits[[i]] <- fit
      limmat[not.nas, i] <- fit$t[, 2]
      limmas2[i] <- fit$s2.prior
      limmadf[i] <- fit$df.prior
      limmav0[i] <- fit$var.prior[2]
      limmag1num[i] <- g1num
      limmag2num[i] <- g2num
    }
    limmacompnum <- nrow(compid)
    names(limmafits) <- rownames(compid)
    result <- list(t       = limmat,
                   v0      = limmav0,
                   df0     = limmadf,
                   s20     = limmas2,
                   g1num   = limmag1num,
                   g2num   = limmag2num,
                   compnum = limmacompnum,
                   fits    = limmafits)
  }

limmafit.list <-
  function (fitlist, cmp.idx=2)
  {
    compnum    <- length(fitlist)

    genes <- c()
    for (i in 1:compnum) genes <- unique(c(genes, rownames(fitlist[[i]])))

    genenum    <- length(genes)
    limmat     <- matrix(NA,genenum,compnum)
    limmas2    <- rep(0,compnum)
    limmadf    <- rep(0,compnum)
    limmav0    <- rep(0,compnum)
    limmag1num <- rep(0,compnum)
    limmag2num <- rep(0,compnum)

    rownames(limmat)  <- genes
    colnames(limmat)  <- names(fitlist)
    names(limmas2)    <- names(fitlist)
    names(limmadf)    <- names(fitlist)
    names(limmav0)    <- names(fitlist)
    names(limmag1num) <- names(fitlist)
    names(limmag2num) <- names(fitlist)

    for (i in 1:compnum) {
      this.t <- fitlist[[i]]$t[,cmp.idx]
      limmat[names(this.t),i] <- this.t

      limmas2[i]    <- fitlist[[i]]$s2.prior
      limmadf[i]    <- fitlist[[i]]$df.prior
      limmav0[i]    <- fitlist[[i]]$var.prior[cmp.idx]
      limmag1num[i] <- sum(fitlist[[i]]$design[,cmp.idx]==0)
      limmag2num[i] <- sum(fitlist[[i]]$design[,cmp.idx]==1)
    }

    limmacompnum <- compnum
    result <- list(t       = limmat,
                   v0      = limmav0,
                   df0     = limmadf,
                   s20     = limmas2,
                   g1num   = limmag1num,
                   g2num   = limmag2num,
                   compnum = limmacompnum,
                   fits    = limmafits)

  }

## Rank genes based on statistics
generank<-function(x) {
  xcol<-ncol(x)
  xrow<-nrow(x)
  result<-matrix(0,xrow,xcol)
  z<-(1:1:xrow)
  for(i in 1:xcol) {
    y<-sort(x[,i],decreasing=TRUE,na.last=TRUE)
    result[,i]<-match(x[,i],y)
    result[,i]<-order(result[,i])
  }
  result
}

## Log-likelihood for moderated t under H0
modt.f0.loglike<-function(x,df) {
  a<-dt(x, df, log=TRUE)
  result<-as.vector(a)
  flag<-which(is.na(result)==TRUE)
  result[flag]<-0
  result
}

## Log-likelihood for moderated t under H1
## param=c(df,g1num,g2num,v0)
modt.f1.loglike<-function(x,param) {
  df<-param[1]
  g1num<-param[2]
  g2num<-param[3]
  v0<-param[4]
  w<-sqrt(1+v0/(1/g1num+1/g2num))
  dt(x/w, df, log=TRUE)-log(w)
  a<-dt(x/w, df, log=TRUE)-log(w)
  result<-as.vector(a)
  flag<-which(is.na(result)==TRUE)
  result[flag]<-0
  result
}

## Correlation Motif Fit
cmfit.X<-function(x, type, K=1, tol=1e-3, max.iter=100) {
  ## initialize
  xrow <- nrow(x)
  xcol <- ncol(x)
  loglike0 <- list()
  loglike1 <- list()
  p <- rep(1, K)/K
  q <- matrix(runif(K * xcol), K, xcol)
  q[1, ] <- rep(0.01, xcol)
  for (i in 1:xcol) {
    f0 <- type[[i]][[1]]
    f0param <- type[[i]][[2]]
    f1 <- type[[i]][[3]]
    f1param <- type[[i]][[4]]
    loglike0[[i]] <- f0(x[, i], f0param)
    loglike1[[i]] <- f1(x[, i], f1param)
  }
  condlike <- list()
  for (i in 1:xcol) {
    condlike[[i]] <- matrix(0, xrow, K)
  }
  loglike.old <- -1e+10
  for (i.iter in 1:max.iter) {
    if ((i.iter%%50) == 0) {
      print(paste("We have run the first ", i.iter, " iterations for K=",
                  K, sep = ""))
    }
    err <- tol + 1
    clustlike <- matrix(0, xrow, K)
    #templike <- matrix(0, xrow, 2)
    templike1 <- rep(0, xrow)
    templike2 <- rep(0, xrow)
    for (j in 1:K) {
      for (i in 1:xcol) {
        templike1 <- log(q[j, i]) + loglike1[[i]]
        templike2 <- log(1 - q[j, i]) + loglike0[[i]]
        tempmax <- Rfast::Pmax(templike1, templike2)

        templike1 <- exp(templike1 - tempmax)
        templike2 <- exp(templike2 - tempmax)

        tempsum <- templike1 + templike2
        clustlike[, j] <- clustlike[, j] + tempmax +
          log(tempsum)
        condlike[[i]][, j] <- templike1/tempsum
      }
      clustlike[, j] <- clustlike[, j] + log(p[j])
    }
    #tempmax <- apply(clustlike, 1, max)
    tempmax <- Rfast::rowMaxs(clustlike, value=TRUE)
    for (j in 1:K) {
      clustlike[, j] <- exp(clustlike[, j] - tempmax)
    }
    #tempsum <- apply(clustlike, 1, sum)
    tempsum <- Rfast::rowsums(clustlike)
    for (j in 1:K) {
      clustlike[, j] <- clustlike[, j]/tempsum
    }
    #p.new <- (apply(clustlike, 2, sum) + 1)/(xrow + K)
    p.new <- (Rfast::colsums(clustlike) + 1)/(xrow + K)
    q.new <- matrix(0, K, xcol)
    for (j in 1:K) {
      clustpsum <- sum(clustlike[, j])
      for (i in 1:xcol) {
        q.new[j, i] <- (sum(clustlike[, j] * condlike[[i]][,
                                                           j]) + 1)/(clustpsum + 2)
      }
    }
    err.p <- max(abs(p.new - p)/p)
    err.q <- max(abs(q.new - q)/q)
    err <- max(err.p, err.q)
    loglike.new <- (sum(tempmax + log(tempsum)) + sum(log(p.new)) +
                      sum(log(q.new) + log(1 - q.new)))/xrow
    p <- p.new
    q <- q.new
    loglike.old <- loglike.new
    if (err < tol) {
      break
    }
  }
  clustlike <- matrix(0, xrow, K)
  for (j in 1:K) {
    for (i in 1:xcol) {
      templike1 <- log(q[j, i]) + loglike1[[i]]
      templike2 <- log(1 - q[j, i]) + loglike0[[i]]
      tempmax <- Rfast::Pmax(templike1, templike2)

      templike1 <- exp(templike1 - tempmax)
      templike2 <- exp(templike2 - tempmax)

      tempsum <- templike1 + templike2
      clustlike[, j] <- clustlike[, j] + tempmax + log(tempsum)
      condlike[[i]][, j] <- templike1/tempsum
    }
    clustlike[, j] <- clustlike[, j] + log(p[j])
  }
  #tempmax <- apply(clustlike, 1, max)
  tempmax <- Rfast::rowMaxs(clustlike, value=TRUE)
  for (j in 1:K) {
    clustlike[, j] <- exp(clustlike[, j] - tempmax)
  }
  #tempsum <- apply(clustlike, 1, sum)
  tempsum <- Rfast::rowsums(clustlike)
  for (j in 1:K) {
    clustlike[, j] <- clustlike[, j]/tempsum
  }
  p.post <- matrix(0, xrow, xcol)
  for (j in 1:K) {
    for (i in 1:xcol) {
      p.post[, i] <- p.post[, i] + clustlike[, j] * condlike[[i]][,
                                                                  j]
    }
  }
  loglike.old <- loglike.old - (sum(log(p)) + sum(log(q) +
                                                    log(1 - q)))/xrow
  loglike.old <- loglike.old * xrow
  result <- list(p.post = p.post, motif.prior = p, motif.q = q,
                 loglike = loglike.old, clustlike=clustlike, condlike=condlike)
}

## Fit using (0,0,...,0) and (1,1,...,1)
cmfitall<-function(x, type, tol=1e-3, max.iter=100) {
  ## initialize
  xrow<-nrow(x)
  xcol<-ncol(x)
  loglike0<-list()
  loglike1<-list()
  p<-0.01

  ## compute loglikelihood
  L0<-matrix(0,xrow,1)
  L1<-matrix(0,xrow,1)
  for(i in 1:xcol) {
    f0<-type[[i]][[1]]
    f0param<-type[[i]][[2]]
    f1<-type[[i]][[3]]
    f1param<-type[[i]][[4]]
    loglike0[[i]]<-f0(x[,i],f0param)
    loglike1[[i]]<-f1(x[,i],f1param)
    L0<-L0+loglike0[[i]]
    L1<-L1+loglike1[[i]]
  }


  ## EM algorithm to get MLE of p and q
  loglike.old <- -1e10
  for(i.iter in 1:max.iter) {
    if((i.iter%%50) == 0) {
      print(paste("We have run the first ", i.iter, " iterations",sep=""))
    }
    err<-tol+1

    ## compute posterior cluster membership
    clustlike<-matrix(0,xrow,2)
    clustlike[,1]<-log(1-p)+L0
    clustlike[,2]<-log(p)+L1

    tempmax<-apply(clustlike,1,max)
    for(j in 1:2) {
      clustlike[,j]<-exp(clustlike[,j]-tempmax)
    }
    tempsum<-apply(clustlike,1,sum)

    ## update motif occurrence rate
    for(j in 1:2) {
      clustlike[,j]<-clustlike[,j]/tempsum
    }

    p.new<-(sum(clustlike[,2])+1)/(xrow+2)

    ## evaluate convergence
    err<-abs(p.new-p)/p

    ## evaluate whether the log.likelihood increases
    loglike.new<-(sum(tempmax+log(tempsum))+log(p.new)+log(1-p.new))/xrow

    loglike.old<-loglike.new
    p<-p.new

    if(err<tol) {
      break;
    }
  }

  ## compute posterior p
  clustlike<-matrix(0,xrow,2)
  clustlike[,1]<-log(1-p)+L0
  clustlike[,2]<-log(p)+L1

  tempmax<-apply(clustlike,1,max)
  for(j in 1:2) {
    clustlike[,j]<-exp(clustlike[,j]-tempmax)
  }
  tempsum<-apply(clustlike,1,sum)

  for(j in 1:2) {
    clustlike[,j]<-clustlike[,j]/tempsum
  }

  p.post<-matrix(0,xrow,xcol)
  for(i in 1:xcol) {
    p.post[,i]<-clustlike[,2]
  }

  ## return

  #calculate back loglikelihood
  loglike.old<-loglike.old-(log(p)+log(1-p))/xrow
  loglike.old<-loglike.old*xrow
  result<-list(p.post=p.post, motif.prior=p, loglike=loglike.old)
}

## Fit each dataset separately
cmfitsep<-function(x, type, tol=1e-3, max.iter=100) {
  ## initialize
  xrow<-nrow(x)
  xcol<-ncol(x)
  loglike0<-list()
  loglike1<-list()
  p<-0.01*rep(1,xcol)
  loglike.final<-rep(0,xcol)

  ## compute loglikelihood
  for(i in 1:xcol) {
    f0<-type[[i]][[1]]
    f0param<-type[[i]][[2]]
    f1<-type[[i]][[3]]
    f1param<-type[[i]][[4]]
    loglike0[[i]]<-f0(x[,i],f0param)
    loglike1[[i]]<-f1(x[,i],f1param)
  }

  p.post<-matrix(0,xrow,xcol)

  ## EM algorithm to get MLE of p
  for(coli in 1:xcol) {
    loglike.old <- -1e10
    for(i.iter in 1:max.iter) {
      if((i.iter%%50) == 0) {
        print(paste("We have run the first ", i.iter, " iterations",sep=""))
      }
      err<-tol+1

      ## compute posterior cluster membership
      clustlike<-matrix(0,xrow,2)
      clustlike[,1]<-log(1-p[coli])+loglike0[[coli]]
      clustlike[,2]<-log(p[coli])+loglike1[[coli]]

      tempmax<-apply(clustlike,1,max)
      for(j in 1:2) {
        clustlike[,j]<-exp(clustlike[,j]-tempmax)
      }
      tempsum<-apply(clustlike,1,sum)

      ## evaluate whether the log.likelihood increases
      loglike.new<-sum(tempmax+log(tempsum))/xrow

      ## update motif occurrence rate
      for(j in 1:2) {
        clustlike[,j]<-clustlike[,j]/tempsum
      }

      p.new<-(sum(clustlike[,2]))/(xrow)

      ## evaluate convergence
      err<-abs(p.new-p[coli])/p[coli]
      loglike.old<-loglike.new
      p[coli]<-p.new

      if(err<tol) {
        break;
      }
    }

    ## compute posterior p
    clustlike<-matrix(0,xrow,2)
    clustlike[,1]<-log(1-p[coli])+loglike0[[coli]]
    clustlike[,2]<-log(p[coli])+loglike1[[coli]]

    tempmax<-apply(clustlike,1,max)
    for(j in 1:2) {
      clustlike[,j]<-exp(clustlike[,j]-tempmax)
    }
    tempsum<-apply(clustlike,1,sum)

    for(j in 1:2) {
      clustlike[,j]<-clustlike[,j]/tempsum
    }

    p.post[,coli]<-clustlike[,2]
    loglike.final[coli]<-loglike.old
  }


  ## return
  loglike.final<-loglike.final*xrow
  result<-list(p.post=p.post, motif.prior=p, loglike=loglike.final)
}

## Fit the full model
cmfitfull<-function(x, type, tol=1e-3, max.iter=100) {
  ## initialize
  xrow<-nrow(x)
  xcol<-ncol(x)
  loglike0<-list()
  loglike1<-list()
  K<-2^xcol
  p<-rep(1,K)/K
  pattern<-rep(0,xcol)
  patid<-matrix(0,K,xcol)

  ## compute loglikelihood
  for(i in 1:xcol) {
    f0<-type[[i]][[1]]
    f0param<-type[[i]][[2]]
    f1<-type[[i]][[3]]
    f1param<-type[[i]][[4]]
    loglike0[[i]]<-f0(x[,i],f0param)
    loglike1[[i]]<-f1(x[,i],f1param)
  }
  L<-matrix(0,xrow,K)
  for(i in 1:K)
  {
    patid[i,]<-pattern
    for(j in 1:xcol) {
      if(pattern[j] < 0.5) {
        L[,i]<-L[,i]+loglike0[[j]]
      } else {
        L[,i]<-L[,i]+loglike1[[j]]
      }
    }

    if(i < K) {
      pattern[xcol]<-pattern[xcol]+1
      j<-xcol
      while(pattern[j] > 1) {
        pattern[j]<-0
        j<-j-1
        pattern[j]<-pattern[j]+1
      }
    }
  }

  ## EM algorithm to get MLE of p and q
  loglike.old <- -1e10
  for(i.iter in 1:max.iter) {
    if((i.iter%%50) == 0) {
      print(paste("We have run the first ", i.iter, " iterations",sep=""))
    }
    err<-tol+1

    ## compute posterior cluster membership
    clustlike<-matrix(0,xrow,K)
    for(j in 1:K) {
      clustlike[,j]<-log(p[j])+L[,j]
    }

    tempmax<-apply(clustlike,1,max)
    for(j in 1:K) {
      clustlike[,j]<-exp(clustlike[,j]-tempmax)
    }
    tempsum<-apply(clustlike,1,sum)

    ## update motif occurrence rate
    for(j in 1:K) {
      clustlike[,j]<-clustlike[,j]/tempsum
    }

    p.new<-(apply(clustlike,2,sum)+1)/(xrow+K)

    ## evaluate convergence
    err<-max(abs(p.new-p)/p)

    ## evaluate whether the log.likelihood increases
    loglike.new<-(sum(tempmax+log(tempsum))+sum(log(p.new)))/xrow

    loglike.old<-loglike.new
    p<-p.new

    if(err<tol) {
      break;
    }
  }

  ## compute posterior p
  clustlike<-matrix(0,xrow,K)
  for(j in 1:K) {
    clustlike[,j]<-log(p[j])+L[,j]
  }

  tempmax<-apply(clustlike,1,max)
  for(j in 1:K) {
    clustlike[,j]<-exp(clustlike[,j]-tempmax)
  }
  tempsum<-apply(clustlike,1,sum)

  for(j in 1:K) {
    clustlike[,j]<-clustlike[,j]/tempsum
  }

  p.post<-matrix(0,xrow,xcol)
  for(j in 1:K) {
    for(i in 1:xcol) {
      if(patid[j,i] > 0.5) {
        p.post[,i]<-p.post[,i]+clustlike[,j]
      }
    }
  }

  ## return
  #calculate back loglikelihood
  loglike.old<-loglike.old-sum(log(p))/xrow
  loglike.old<-loglike.old*xrow
  result<-list(p.post=p.post, motif.prior=p, loglike=loglike.old)
}

generatetype<-function(limfitted)
{
  jtype<-list()
  df<-limfitted$g1num+limfitted$g2num-2+limfitted$df0
  for(j in 1:limfitted$compnum)
  {
    jtype[[j]]<-list(f0=modt.f0.loglike, f0.param=df[j], f1=modt.f1.loglike, f1.param=c(df[j],limfitted$g1num[j],limfitted$g2num[j],limfitted$v0[j]))
  }
  jtype
}

cormotiffit <- function(exprs, groupid=NULL, compid=NULL, K=1, tol=1e-3,
                        max.iter=100, BIC=TRUE, norm.factor.method="TMM",
                        voom.normalize.method = "none", runtype=c("logCPM","counts","limmafits"), each=3)
{
  # first I want to do some typechecking. Input can be either a normalized
  # matrix, a count matrix, or a list of limma fits. Dispatch the correct
  # limmafit accordingly.
  # todo: add some typechecking here
  limfitted <- list()
  if (runtype=="counts") {
    limfitted <- limmafit.counts(exprs,groupid,compid, norm.factor.method, voom.normalize.method)
  } else if (runtype=="logCPM") {
    limfitted <- limmafit.default(exprs,groupid,compid)
  } else if (runtype=="limmafits") {
    limfitted <- limmafit.list(exprs)
  } else {
    stop("runtype must be one of 'logCPM', 'counts', or 'limmafits'")
  }


  jtype<-generatetype(limfitted)
  fitresult<-list()
  ks <- rep(K, each = each)
  fitresult <- bplapply(1:length(ks), function(i, x, type, ks, tol, max.iter) {
    cmfit.X(x, type, K = ks[i], tol = tol, max.iter = max.iter)
  }, x=limfitted$t, type=jtype, ks=ks, tol=tol, max.iter=max.iter)

  best.fitresults <- list()
  for (i in 1:length(K)) {
    w.k <- which(ks==K[i])
    this.bic <- c()
    for (j in w.k) this.bic[j] <- -2 * fitresult[[j]]$loglike + (K[i] - 1 + K[i] * limfitted$compnum) * log(dim(limfitted$t)[1])
    w.min <- which(this.bic == min(this.bic, na.rm = TRUE))[1]
    best.fitresults[[i]] <- fitresult[[w.min]]
  }
  fitresult <- best.fitresults

  bic <- rep(0, length(K))
  aic <- rep(0, length(K))
  loglike <- rep(0, length(K))
  for (i in 1:length(K)) loglike[i] <- fitresult[[i]]$loglike
  for (i in 1:length(K)) bic[i] <- -2 * fitresult[[i]]$loglike + (K[i] - 1 + K[i] * limfitted$compnum) * log(dim(limfitted$t)[1])
  for (i in 1:length(K)) aic[i] <- -2 * fitresult[[i]]$loglike + 2 * (K[i] - 1 + K[i] * limfitted$compnum)
  if(BIC==TRUE) {
    bestflag=which(bic==min(bic))
  }
  else {
    bestflag=which(aic==min(aic))
  }
  result<-list(bestmotif=fitresult[[bestflag]],bic=cbind(K,bic),
               aic=cbind(K,aic),loglike=cbind(K,loglike), allmotifs=fitresult)

}

cormotiffitall<-function(exprs,groupid,compid, tol=1e-3, max.iter=100)
{
  limfitted<-limmafit(exprs,groupid,compid)
  jtype<-generatetype(limfitted)
  fitresult<-cmfitall(limfitted$t,type=jtype,tol=1e-3,max.iter=max.iter)
}

cormotiffitsep<-function(exprs,groupid,compid, tol=1e-3, max.iter=100)
{
  limfitted<-limmafit(exprs,groupid,compid)
  jtype<-generatetype(limfitted)
  fitresult<-cmfitsep(limfitted$t,type=jtype,tol=1e-3,max.iter=max.iter)
}

cormotiffitfull<-function(exprs,groupid,compid, tol=1e-3, max.iter=100)
{
  limfitted<-limmafit(exprs,groupid,compid)
  jtype<-generatetype(limfitted)
  fitresult<-cmfitfull(limfitted$t,type=jtype,tol=1e-3,max.iter=max.iter)
}

plotIC<-function(fitted_cormotif)
{
  oldpar<-par(mfrow=c(1,2))
  plot(fitted_cormotif$bic[,1], fitted_cormotif$bic[,2], type="b",xlab="Motif Number", ylab="BIC", main="BIC")
  plot(fitted_cormotif$aic[,1], fitted_cormotif$aic[,2], type="b",xlab="Motif Number", ylab="AIC", main="AIC")
}

plotMotif<-function(fitted_cormotif,title="")
{
  layout(matrix(1:2,ncol=2))
  u<-1:dim(fitted_cormotif$bestmotif$motif.q)[2]
  v<-1:dim(fitted_cormotif$bestmotif$motif.q)[1]
  image(u,v,t(fitted_cormotif$bestmotif$motif.q),
        col=gray(seq(from=1,to=0,by=-0.1)),xlab="Study",yaxt = "n",
        ylab="Corr. Motifs",main=paste(title,"pattern",sep=" "))
  axis(2,at=1:length(v))
  for(i in 1:(length(u)+1))
  {
    abline(v=(i-0.5))
  }
  for(i in 1:(length(v)+1))
  {
    abline(h=(i-0.5))
  }
  Ng=10000
  if(is.null(fitted_cormotif$bestmotif$p.post)!=TRUE)
    Ng=nrow(fitted_cormotif$bestmotif$p.post)
  genecount=floor(fitted_cormotif$bestmotif$motif.p*Ng)
  NK=nrow(fitted_cormotif$bestmotif$motif.q)
  plot(0,0.7,pch=".",xlim=c(0,1.2),ylim=c(0.75,NK+0.25),
       frame.plot=FALSE,axes=FALSE,xlab="No. of genes",ylab="", main=paste(title,"frequency",sep=" "))
  segments(0,0.7,fitted_cormotif$bestmotif$motif.p[1],0.7)
  rect(0,1:NK-0.3,fitted_cormotif$bestmotif$motif.p,1:NK+0.3,
       col="dark grey")
  mtext(1:NK,at=1:NK,side=2,cex=0.8)
  text(fitted_cormotif$bestmotif$motif.p+0.15,1:NK,
       labels=floor(fitted_cormotif$bestmotif$motif.p*Ng))
}
library(edgeR)
library(Cormotif)
library(RColorBrewer)

library(BiocParallel)
## read in count file##
design <- read.csv("data/data_outline.txt", row.names = 1)
mymatrix <- readRDS("data/filtermatrix_x.RDS")#should be 14084
x_counts <- mymatrix$counts

indv <- as.factor(rep(c(1,2,3,4,5,6), c(12,12,12,12,12,12)))
time <- rep((rep(c("3h", "24h"), c(6,6))), 6)
time <- ordered(time, levels =c("3h", "24h"))
group <- as.factor(rep((c("1","2","3","4","5","6","7","8","9","10","11","12")),6))
drug <- rep(c("Daunorubicin","Doxorubicin","Epirubicin","Mitoxantrone","Trastuzumab", "Vehicle"),12)
group1 <- interaction(drug,time)
label <- (interaction(substring(drug, 0, 2), indv, time))
colnames(x_counts) <- label
group_fac <- group1
groupid <- as.numeric(group_fac)

compid <- data.frame(c1= c(1,2,3,4,5,7,8,9,10,11), c2 = c( 6,6,6,6,6,12,12,12,12,12))

y_TMM_cpm <- cpm(x_counts, log = TRUE)

colnames(y_TMM_cpm) <- label
y_TMM_cpm
set.seed(12345)
cormotif_initial <- cormotiffit(exprs = y_TMM_cpm,
                             groupid = groupid,
                             compid = compid,
                             K=1:8, max.iter = 500,runtype="logCPM")
gene_prob_tran <- cormotif_initial$bestmotif$p.post
rownames(gene_prob_tran) <- rownames(y_TMM_cpm)
motif_prob <- cormotif_initial$bestmotif$clustlike
rownames(motif_prob) <- rownames(y_TMM_cpm)
write.csv(motif_prob,"cormotif_probability_genelist.csv")

cormotif_initial was created after calling corMotif, then running the corMotifcustom.R script. The extra R script enabled me to generate a table containing the likelihood of each gene that belongs to the specific cluster.

After generating the Motifs from 1 to 8, the number of motifs that best fit the data was 4 using the BIC and AIC results below.

cormotif_initial <- readRDS("data/cormotif_initialall.RDS")#
plotIC(cormotif_initial)

plotMotif(cormotif_initial)

Viewing the motifs, the following groups were named:

  • Motif 1: No Response (n=7409)

  • Motif 2: Top2\(\beta\) inhibitor response, Time-independent

    • (Time-independent response, n= 589)
  • Motif 3: Top2\(\beta\) inhibitor response, Early

    • (Early response, n= 487)
  • Motif 4: Top2\(\beta\) inhibitor response, Late

    • (Late response, n= 5596)
clust1 <- motif_prob %>%
  as.data.frame() %>%
  filter(V1>0.5) %>% 
  rownames
clust2 <- motif_prob %>%
  as.data.frame() %>%
  filter(V2>0.5) %>% 
  rownames
clust3 <- motif_prob %>%
  as.data.frame() %>%
  filter(V3>0.5) %>% 
  rownames
clust4 <- motif_prob %>%
  as.data.frame() %>%
  filter(V4>0.5) %>% 
  rownames
old_clust1  <- rownames(gene_prob_tran[(gene_prob_tran[,1] <0.45 &
                                          gene_prob_tran[,2] <0.45 &
                                          gene_prob_tran[,3] <0.45 &
                                          gene_prob_tran[,4] <0.45 &
                                          gene_prob_tran[,5] <0.45 &
                                          gene_prob_tran[,6] <0.45 &
                                          gene_prob_tran[,7] <0.45 &
                                          gene_prob_tran[,8] <0.45 &
                                          gene_prob_tran[,9] <0.45 &
                                         gene_prob_tran[,10] <0.45),])
length(intersect(old_clust1,clust1))##7358 out of 7362 oldclust1

old_clust2  <- rownames(gene_prob_tran[(gene_prob_tran[,1]> 0.10 &
                                         gene_prob_tran[,2] > 0.10 &
                                         gene_prob_tran[,3] > 0.10 &
                                         gene_prob_tran[,4] > 0.10 &
                                         # gene_prob_tran[,5] < 0.10 &
                                           gene_prob_tran[,6] > 0.10&
                                           gene_prob_tran[,7]> 0.10 &
                                           gene_prob_tran[,8]> 0.10 &
                                           gene_prob_tran[,9]> 0.10),])
# &                                      # gene_prob_tran[,10]< 0.10),])
                                                   
length(intersect(old_clust2,clust2))##251 out of 432 oldclust2

old_clust3 <- rownames(gene_prob_tran[(gene_prob_tran[,1]>0.55 &
                                           gene_prob_tran[,2] >0.55 &
                                           gene_prob_tran[,3] >0.55 &
                                           gene_prob_tran[,4] >0.25&
                                           gene_prob_tran[,5] <0.90 &
                                           gene_prob_tran[,6] <0.9 &
                                           gene_prob_tran[,7]<0.9&
                                           gene_prob_tran[,8]<0.9 &
                                          gene_prob_tran[,9]<0.9 &
                                           gene_prob_tran[,10]<0.90),])
length(intersect(old_clust3,clust3)) ##414 out of 481 oldclust3

old_clust4 <- rownames(gene_prob_tran[(gene_prob_tran[,1] <0.970 &
                                            gene_prob_tran[,2] <0.97 &
                                            gene_prob_tran[,3] <0.97 &
                                            gene_prob_tran[,4] <0.97 &
                                            gene_prob_tran[,5] <0.9&
                                            gene_prob_tran[,6] >0.55 &
                                            gene_prob_tran[,7] >0.55 &
                                            gene_prob_tran[,8] >0.55 &
                                            gene_prob_tran[,9] >0.05 &
                                            gene_prob_tran[,10] <0.9),])
length(intersect(old_clust4,clust4))##4675 out of 4850 oldclust4
backGL <- read.csv("data/backGL.txt")  ##14084
length(setdiff(backGL$ENTREZID,(union(clust1,union(clust2,union(clust3,clust4))))))
##63 genes not used overall  same as (14084-7504-528-444-5545)

There was overlap between the previous sets and the new sets, so I moved on expecting similar responses in the GO analysis. I did subset out the genes not used overall from the background gene list (rowmeans>0 from log(cpm(count matrix)))

DEG_cormotif <- readRDS("data/DEG_cormotif.RDS")
motif_NR <- DEG_cormotif$motif_NR
motif_TI <- DEG_cormotif$motif_TI
motif_LR <- DEG_cormotif$motif_LR
motif_ER <- DEG_cormotif$motif_ER
  
backGL <- read.csv("data/backGL.txt")
#NRresp <- read_csv("data/cormotif_NRset.txt")

No response motif genes

source term_id term_name intersection_size term_size p_value
GO:BP GO:0002181 cytoplasmic translation 117 155 9.02e-06
GO:BP GO:0019646 aerobic electron transport chain 63 74 9.02e-06
GO:BP GO:0009060 aerobic respiration 133 180 9.02e-06
GO:BP GO:0006119 oxidative phosphorylation 104 134 9.02e-06
GO:BP GO:0022904 respiratory electron transport chain 83 103 9.02e-06
GO:BP GO:0042775 mitochondrial ATP synthesis coupled electron transport 68 82 1.51e-05
GO:BP GO:0042773 ATP synthesis coupled electron transport 68 82 1.51e-05
GO:BP GO:0045333 cellular respiration 158 222 1.67e-05
GO:BP GO:0034645 cellular macromolecule biosynthetic process 624 1030 8.49e-05
GO:BP GO:1901566 organonitrogen compound biosynthetic process 878 1499 7.73e-04
GO:BP GO:0009100 glycoprotein metabolic process 209 317 1.00e-03
GO:BP GO:0022900 electron transport chain 102 141 1.29e-03
GO:BP GO:1901564 organonitrogen compound metabolic process 2774 5018 1.40e-03
GO:BP GO:0043603 amide metabolic process 597 999 1.44e-03
GO:BP GO:0006518 peptide metabolic process 481 793 1.50e-03
GO:BP GO:0015980 energy derivation by oxidation of organic compounds 196 298 1.91e-03
GO:BP GO:0070085 glycosylation 139 204 2.73e-03
GO:BP GO:0033108 mitochondrial respiratory chain complex assembly 71 94 2.73e-03
GO:BP GO:0006486 protein glycosylation 130 189 2.73e-03
GO:BP GO:0043413 macromolecule glycosylation 130 189 2.73e-03
GO:BP GO:0006412 translation 393 644 4.10e-03
GO:BP GO:0006091 generation of precursor metabolites and energy 272 432 4.10e-03
GO:BP GO:0022613 ribonucleoprotein complex biogenesis 281 449 5.52e-03
GO:BP GO:0019538 protein metabolic process 2347 4252 1.54e-02
GO:BP GO:0015986 proton motive force-driven ATP synthesis 51 66 1.54e-02
GO:BP GO:0043043 peptide biosynthetic process 400 664 1.54e-02
GO:BP GO:0043604 amide biosynthetic process 458 767 1.54e-02
GO:BP GO:0009101 glycoprotein biosynthetic process 165 254 1.87e-02
GO:BP GO:0006487 protein N-linked glycosylation 50 65 2.02e-02
GO:BP GO:0006754 ATP biosynthetic process 64 87 2.10e-02
GO:BP GO:1901135 carbohydrate derivative metabolic process 529 899 2.68e-02
GO:BP GO:0010257 NADH dehydrogenase complex assembly 43 55 3.07e-02
GO:BP GO:0032981 mitochondrial respiratory chain complex I assembly 43 55 3.07e-02
GO:BP GO:0010466 negative regulation of peptidase activity 101 149 4.20e-02
GO:BP GO:0042776 proton motive force-driven mitochondrial ATP synthesis 44 57 4.20e-02
KEGG KEGG:05171 Coronavirus disease - COVID-19 122 162 7.18e-07
KEGG KEGG:03010 Ribosome 98 127 1.54e-06
KEGG KEGG:04510 Focal adhesion 126 175 9.65e-06
KEGG KEGG:05208 Chemical carcinogenesis - reactive oxygen species 133 186 9.65e-06
KEGG KEGG:00190 Oxidative phosphorylation 81 106 2.52e-05
KEGG KEGG:04512 ECM-receptor interaction 55 69 1.36e-04
KEGG KEGG:05012 Parkinson disease 153 226 1.36e-04
KEGG KEGG:04714 Thermogenesis 134 195 1.39e-04
KEGG KEGG:05020 Prion disease 148 220 2.52e-04
KEGG KEGG:05415 Diabetic cardiomyopathy 117 169 2.64e-04
KEGG KEGG:00531 Glycosaminoglycan degradation 16 16 1.02e-03
KEGG KEGG:04141 Protein processing in endoplasmic reticulum 110 161 1.02e-03
KEGG KEGG:05016 Huntington disease 165 256 2.07e-03
KEGG KEGG:05010 Alzheimer disease 197 315 5.40e-03
KEGG KEGG:00513 Various types of N-glycan biosynthesis 29 36 1.08e-02
KEGG KEGG:04932 Non-alcoholic fatty liver disease 88 131 1.08e-02
KEGG KEGG:04142 Lysosome 80 118 1.17e-02
KEGG KEGG:00510 N-Glycan biosynthesis 36 48 2.41e-02
KEGG KEGG:04810 Regulation of actin cytoskeleton 114 179 3.22e-02
KEGG KEGG:01200 Carbon metabolism 66 98 3.80e-02
KEGG KEGG:03040 Spliceosome 86 132 3.93e-02
KEGG KEGG:05022 Pathways of neurodegeneration - multiple diseases 230 385 4.28e-02

Late response Top2\(\beta\) inhibitor motif genes

source term_id term_name intersection_size term_size p_value
GO:BP GO:0007059 chromosome segregation 207 378 4.07e-06
GO:BP GO:0000280 nuclear division 190 354 8.76e-05
GO:BP GO:0051301 cell division 284 567 1.73e-04
GO:BP GO:0007049 cell cycle 689 1522 4.11e-04
GO:BP GO:0098813 nuclear chromosome segregation 155 287 4.42e-04
GO:BP GO:0007051 spindle organization 107 186 5.13e-04
GO:BP GO:0000070 mitotic sister chromatid segregation 110 193 5.75e-04
GO:BP GO:0140014 mitotic nuclear division 143 264 6.50e-04
GO:BP GO:0006261 DNA-templated DNA replication 88 149 7.42e-04
GO:BP GO:0048285 organelle fission 203 397 7.42e-04
GO:BP GO:0061982 meiosis I cell cycle process 53 80 8.85e-04
GO:BP GO:0022402 cell cycle process 495 1075 9.31e-04
GO:BP GO:0140013 meiotic nuclear division 73 121 1.68e-03
GO:BP GO:0000278 mitotic cell cycle 390 833 1.71e-03
GO:BP GO:0007127 meiosis I 50 76 1.81e-03
GO:BP GO:1903046 meiotic cell cycle process 80 136 1.85e-03
GO:BP GO:0000226 microtubule cytoskeleton organization 268 552 2.03e-03
GO:BP GO:0000819 sister chromatid segregation 126 234 2.07e-03
GO:BP GO:0045132 meiotic chromosome segregation 46 69 2.09e-03
GO:BP GO:1903047 mitotic cell cycle process 331 700 2.51e-03
GO:BP GO:0051276 chromosome organization 261 543 5.74e-03
GO:BP GO:0007017 microtubule-based process 352 756 6.39e-03
GO:BP GO:0006260 DNA replication 134 258 9.24e-03
GO:BP GO:2001251 negative regulation of chromosome organization 55 90 9.83e-03
GO:BP GO:0070925 organelle assembly 370 803 1.06e-02
GO:BP GO:0051716 cellular response to stimulus 2043 4935 1.14e-02
GO:BP GO:0050896 response to stimulus 2360 5741 1.35e-02
GO:BP GO:0032465 regulation of cytokinesis 49 79 1.35e-02
GO:BP GO:1902850 microtubule cytoskeleton organization involved in mitosis 86 156 1.45e-02
GO:BP GO:0045930 negative regulation of mitotic cell cycle 110 208 1.45e-02
GO:BP GO:0045839 negative regulation of mitotic nuclear division 36 54 1.49e-02
GO:BP GO:2000816 negative regulation of mitotic sister chromatid separation 32 47 1.89e-02
GO:BP GO:0033048 negative regulation of mitotic sister chromatid segregation 32 47 1.89e-02
GO:BP GO:0046474 glycerophospholipid biosynthetic process 101 190 1.89e-02
GO:BP GO:0033046 negative regulation of sister chromatid segregation 32 47 1.89e-02
GO:BP GO:0008654 phospholipid biosynthetic process 122 236 1.89e-02
GO:BP GO:0045017 glycerolipid biosynthetic process 114 219 2.09e-02
GO:BP GO:0006996 organelle organization 1253 2971 2.23e-02
GO:BP GO:0051784 negative regulation of nuclear division 37 57 2.23e-02
GO:BP GO:0071174 mitotic spindle checkpoint signaling 30 44 2.59e-02
GO:BP GO:0071173 spindle assembly checkpoint signaling 30 44 2.59e-02
GO:BP GO:0007094 mitotic spindle assembly checkpoint signaling 30 44 2.59e-02
GO:BP GO:0045841 negative regulation of mitotic metaphase/anaphase transition 31 46 2.72e-02
GO:BP GO:1905819 negative regulation of chromosome separation 32 48 2.76e-02
GO:BP GO:0051985 negative regulation of chromosome segregation 32 48 2.76e-02
GO:BP GO:0007093 mitotic cell cycle checkpoint signaling 75 136 2.79e-02
GO:BP GO:0006270 DNA replication initiation 25 35 2.79e-02
GO:BP GO:0033047 regulation of mitotic sister chromatid segregation 34 52 2.85e-02
GO:BP GO:0051304 chromosome separation 45 74 3.10e-02
GO:BP GO:0000075 cell cycle checkpoint signaling 95 180 3.10e-02
GO:BP GO:0007052 mitotic spindle organization 71 128 3.10e-02
GO:BP GO:0021537 telencephalon development 103 198 3.39e-02
GO:BP GO:0051225 spindle assembly 66 118 3.52e-02
GO:BP GO:0031577 spindle checkpoint signaling 30 45 3.79e-02
GO:BP GO:0045786 negative regulation of cell cycle 163 334 3.84e-02
GO:BP GO:1902100 negative regulation of metaphase/anaphase transition of cell cycle 31 47 3.84e-02
GO:BP GO:1901653 cellular response to peptide 139 280 4.26e-02
GO:BP GO:1905818 regulation of chromosome separation 42 69 4.33e-02
GO:BP GO:0051256 mitotic spindle midzone assembly 9 9 4.43e-02
GO:BP GO:0090407 organophosphate biosynthetic process 241 517 4.81e-02
GO:BP GO:0010889 regulation of sequestering of triglyceride 11 12 4.81e-02
GO:BP GO:0019692 deoxyribose phosphate metabolic process 26 38 4.81e-02
GO:BP GO:0051255 spindle midzone assembly 11 12 4.81e-02
GO:BP GO:0009262 deoxyribonucleotide metabolic process 26 38 4.81e-02
KEGG KEGG:00230 Purine metabolism 56 97 2.67e-02
KEGG KEGG:03030 DNA replication 25 35 2.67e-02

Early Response Top2\(\beta\) inhibitor motif genes

query significant p_value term_size query_size intersection_size precision recall term_id source term_name effective_domain_size source_order parents
query_1 TRUE 0.0000000 2683 428 2.16e+02 0.5046729 0.0805069 GO:0006351 GO:BP DNA-templated transcription 13587 2189 GO:0097659
query_1 TRUE 0.0000000 2684 428 2.16e+02 0.5046729 0.0804769 GO:0097659 GO:BP nucleic acid-templated transcription 13587 19903 GO:0010467, GO:0032774
query_1 TRUE 0.0000000 2714 428 2.16e+02 0.5046729 0.0795873 GO:0032774 GO:BP RNA biosynthetic process 13587 8281 GO:0009059, GO:0016070, GO:0034654
query_1 TRUE 0.0000000 1991 428 1.83e+02 0.4275701 0.0919136 GO:0006366 GO:BP transcription by RNA polymerase II 13587 2202 GO:0006351
query_1 TRUE 0.0000000 2581 428 2.09e+02 0.4883178 0.0809764 GO:1903506 GO:BP regulation of nucleic acid-templated transcription 13587 24286 GO:0097659, GO:2001141
query_1 TRUE 0.0000000 3105 428 2.31e+02 0.5397196 0.0743961 GO:0019219 GO:BP regulation of nucleobase-containing compound metabolic process 13587 5932 GO:0006139, GO:0031323, GO:0051171, GO:0080090
query_1 TRUE 0.0000000 2579 428 2.09e+02 0.4883178 0.0810392 GO:0006355 GO:BP regulation of DNA-templated transcription 13587 2193 GO:0006351, GO:0010468, GO:1903506
query_1 TRUE 0.0000000 1915 428 1.78e+02 0.4158879 0.0929504 GO:0006357 GO:BP regulation of transcription by RNA polymerase II 13587 2195 GO:0006355, GO:0006366
query_1 TRUE 0.0000000 2598 428 2.09e+02 0.4883178 0.0804465 GO:2001141 GO:BP regulation of RNA biosynthetic process 13587 27809 GO:0010556, GO:0031326, GO:0032774, GO:0051252
query_1 TRUE 0.0000000 2849 428 2.19e+02 0.5116822 0.0768691 GO:0051252 GO:BP regulation of RNA metabolic process 13587 14451 GO:0016070, GO:0019219, GO:0060255
query_1 TRUE 0.0000000 4047 428 2.60e+02 0.6074766 0.0642451 GO:0090304 GO:BP nucleic acid metabolic process 13587 19342 GO:0006139, GO:0043170
query_1 TRUE 0.0000000 3015 428 2.19e+02 0.5116822 0.0726368 GO:0010556 GO:BP regulation of macromolecule biosynthetic process 13587 4326 GO:0009059, GO:0009889, GO:0060255
query_1 TRUE 0.0000000 3593 428 2.41e+02 0.5630841 0.0670749 GO:0016070 GO:BP RNA metabolic process 13587 5254 GO:0090304
query_1 TRUE 0.0000000 4305 428 2.66e+02 0.6214953 0.0617886 GO:0031323 GO:BP regulation of cellular metabolic process 13587 7549 GO:0019222, GO:0044237, GO:0050794
query_1 TRUE 0.0000000 3083 428 2.19e+02 0.5116822 0.0710347 GO:0034654 GO:BP nucleobase-containing compound biosynthetic process 13587 9218 GO:0006139, GO:0018130, GO:0019438, GO:0044271, GO:1901362
query_1 TRUE 0.0000000 3123 428 2.20e+02 0.5140187 0.0704451 GO:0031326 GO:BP regulation of cellular biosynthetic process 13587 7552 GO:0009889, GO:0031323, GO:0044249
query_1 TRUE 0.0000000 3149 428 2.20e+02 0.5140187 0.0698634 GO:0019438 GO:BP aromatic compound biosynthetic process 13587 6132 GO:0006725, GO:0044249
query_1 TRUE 0.0000000 3148 428 2.20e+02 0.5140187 0.0698856 GO:0018130 GO:BP heterocycle biosynthetic process 13587 5537 GO:0044249, GO:0046483
query_1 TRUE 0.0000000 3174 428 2.20e+02 0.5140187 0.0693132 GO:0009889 GO:BP regulation of biosynthetic process 13587 3843 GO:0009058, GO:0019222
query_1 TRUE 0.0000000 3253 428 2.21e+02 0.5163551 0.0679373 GO:1901362 GO:BP organic cyclic compound biosynthetic process 13587 22499 GO:1901360, GO:1901576
query_1 TRUE 0.0000000 3583 428 2.33e+02 0.5443925 0.0650293 GO:0010468 GO:BP regulation of gene expression 13587 4271 GO:0010467, GO:0060255
query_1 TRUE 0.0000000 4440 428 2.63e+02 0.6144860 0.0592342 GO:0080090 GO:BP regulation of primary metabolic process 13587 18924 GO:0019222, GO:0044238
query_1 TRUE 0.0000000 4330 428 2.59e+02 0.6051402 0.0598152 GO:0051171 GO:BP regulation of nitrogen compound metabolic process 13587 14399 GO:0006807, GO:0019222
query_1 TRUE 0.0000000 3730 428 2.36e+02 0.5514019 0.0632708 GO:0009059 GO:BP macromolecule biosynthetic process 13587 3327 GO:0043170, GO:1901576
query_1 TRUE 0.0000000 4503 428 2.63e+02 0.6144860 0.0584055 GO:0006139 GO:BP nucleobase-containing compound metabolic process 13587 2036 GO:0006725, GO:0034641, GO:0044238, GO:0046483, GO:1901360
query_1 TRUE 0.0000000 4640 428 2.65e+02 0.6191589 0.0571121 GO:0060255 GO:BP regulation of macromolecule metabolic process 13587 15399 GO:0019222, GO:0043170
query_1 TRUE 0.0000000 4616 428 2.64e+02 0.6168224 0.0571924 GO:0046483 GO:BP heterocycle metabolic process 13587 12974 GO:0044237
query_1 TRUE 0.0000000 4646 428 2.64e+02 0.6168224 0.0568231 GO:0006725 GO:BP cellular aromatic compound metabolic process 13587 2497 GO:0044237
query_1 TRUE 0.0000000 3758 428 2.31e+02 0.5397196 0.0614689 GO:0044271 GO:BP cellular nitrogen compound biosynthetic process 13587 11656 GO:0034641, GO:0044249
query_1 TRUE 0.0000000 4790 428 2.66e+02 0.6214953 0.0555324 GO:1901360 GO:BP organic cyclic compound metabolic process 13587 22497 GO:0071704
query_1 TRUE 0.0000000 4572 428 2.58e+02 0.6028037 0.0564304 GO:0010467 GO:BP gene expression 13587 4270 GO:0043170
query_1 TRUE 0.0000000 5039 428 2.73e+02 0.6378505 0.0541774 GO:0019222 GO:BP regulation of metabolic process 13587 5935 GO:0008152, GO:0050789
query_1 TRUE 0.0000000 4991 428 2.68e+02 0.6261682 0.0536967 GO:0034641 GO:BP cellular nitrogen compound metabolic process 13587 9210 GO:0006807, GO:0044237
query_1 TRUE 0.0000000 4465 428 2.49e+02 0.5817757 0.0557671 GO:0044249 GO:BP cellular biosynthetic process 13587 11645 GO:0009058, GO:0044237
query_1 TRUE 0.0000000 4537 428 2.49e+02 0.5817757 0.0548821 GO:1901576 GO:BP organic substance biosynthetic process 13587 22687 GO:0009058, GO:0071704
query_1 TRUE 0.0000000 4595 428 2.49e+02 0.5817757 0.0541893 GO:0009058 GO:BP biosynthetic process 13587 3326 GO:0008152
query_1 TRUE 0.0000000 7057 428 3.22e+02 0.7523364 0.0456285 GO:0043170 GO:BP macromolecule metabolic process 13587 11211 GO:0071704
query_1 TRUE 0.0000000 7579 428 3.29e+02 0.7686916 0.0434094 GO:0050794 GO:BP regulation of cellular process 13587 14091 GO:0009987, GO:0050789
query_1 TRUE 0.0000000 1304 428 1.05e+02 0.2453271 0.0805215 GO:1903508 GO:BP positive regulation of nucleic acid-templated transcription 13587 24288 GO:0097659, GO:1902680, GO:1903506
query_1 TRUE 0.0000000 1304 428 1.05e+02 0.2453271 0.0805215 GO:0045893 GO:BP positive regulation of DNA-templated transcription 13587 12467 GO:0006351, GO:0006355, GO:1903508
query_1 TRUE 0.0000000 1431 428 1.11e+02 0.2593458 0.0775681 GO:0051254 GO:BP positive regulation of RNA metabolic process 13587 14453 GO:0010604, GO:0016070, GO:0045935, GO:0051252
query_1 TRUE 0.0000000 1311 428 1.05e+02 0.2453271 0.0800915 GO:1902680 GO:BP positive regulation of RNA biosynthetic process 13587 23603 GO:0010557, GO:0031328, GO:0032774, GO:0051254, GO:2001141
query_1 TRUE 0.0000000 7503 428 3.25e+02 0.7593458 0.0433160 GO:0044237 GO:BP cellular metabolic process 13587 11638 GO:0008152, GO:0009987
query_1 TRUE 0.0000000 1600 428 1.16e+02 0.2710280 0.0725000 GO:0045935 GO:BP positive regulation of nucleobase-containing compound metabolic process 13587 12505 GO:0006139, GO:0019219, GO:0031325, GO:0051173
query_1 TRUE 0.0000000 7474 428 3.21e+02 0.7500000 0.0429489 GO:0006807 GO:BP nitrogen compound metabolic process 13587 2557 GO:0008152
query_1 TRUE 0.0000000 7992 428 3.35e+02 0.7827103 0.0419169 GO:0050789 GO:BP regulation of biological process 13587 14087 GO:0008150, GO:0065007
query_1 TRUE 0.0000000 7800 428 3.29e+02 0.7686916 0.0421795 GO:0044238 GO:BP primary metabolic process 13587 11639 GO:0008152
query_1 TRUE 0.0000000 8348 428 3.44e+02 0.8037383 0.0412075 GO:0065007 GO:BP biological regulation 13587 16927 GO:0008150
query_1 TRUE 0.0000000 1499 428 1.09e+02 0.2546729 0.0727151 GO:0010557 GO:BP positive regulation of macromolecule biosynthetic process 13587 4327 GO:0009059, GO:0009891, GO:0010556, GO:0010604
query_1 TRUE 0.0000000 1009 428 8.50e+01 0.1985981 0.0842418 GO:0045892 GO:BP negative regulation of DNA-templated transcription 13587 12466 GO:0006351, GO:0006355, GO:1903507
query_1 TRUE 0.0000000 1011 428 8.50e+01 0.1985981 0.0840752 GO:1903507 GO:BP negative regulation of nucleic acid-templated transcription 13587 24287 GO:0097659, GO:1902679, GO:1903506
query_1 TRUE 0.0000000 1020 428 8.50e+01 0.1985981 0.0833333 GO:1902679 GO:BP negative regulation of RNA biosynthetic process 13587 23602 GO:0010558, GO:0031327, GO:0032774, GO:0051253, GO:2001141
query_1 TRUE 0.0000000 1215 428 9.40e+01 0.2196262 0.0773663 GO:0045934 GO:BP negative regulation of nucleobase-containing compound metabolic process 13587 12504 GO:0006139, GO:0019219, GO:0031324, GO:0051172
query_1 TRUE 0.0000000 1115 428 8.90e+01 0.2079439 0.0798206 GO:0051253 GO:BP negative regulation of RNA metabolic process 13587 14452 GO:0010605, GO:0016070, GO:0045934, GO:0051252
query_1 TRUE 0.0000000 925 428 7.90e+01 0.1845794 0.0854054 GO:0045944 GO:BP positive regulation of transcription by RNA polymerase II 13587 12513 GO:0006357, GO:0006366, GO:0045893
query_1 TRUE 0.0000000 1571 428 1.09e+02 0.2546729 0.0693826 GO:0031328 GO:BP positive regulation of cellular biosynthetic process 13587 7554 GO:0009891, GO:0031325, GO:0031326, GO:0044249
query_1 TRUE 0.0000000 8150 428 3.34e+02 0.7803738 0.0409816 GO:0071704 GO:BP organic substance metabolic process 13587 17953 GO:0008152
query_1 TRUE 0.0000000 1598 428 1.09e+02 0.2546729 0.0682103 GO:0009891 GO:BP positive regulation of biosynthetic process 13587 3845 GO:0009058, GO:0009889, GO:0009893
query_1 TRUE 0.0000000 1780 428 1.16e+02 0.2710280 0.0651685 GO:0031324 GO:BP negative regulation of cellular metabolic process 13587 7550 GO:0009892, GO:0031323, GO:0044237, GO:0048523
query_1 TRUE 0.0000000 1206 428 9.00e+01 0.2102804 0.0746269 GO:0010558 GO:BP negative regulation of macromolecule biosynthetic process 13587 4328 GO:0009059, GO:0009890, GO:0010556, GO:0010605
query_1 TRUE 0.0000000 735 428 6.50e+01 0.1518692 0.0884354 GO:0000122 GO:BP negative regulation of transcription by RNA polymerase II 13587 51 GO:0006357, GO:0006366, GO:0045892
query_1 TRUE 0.0000000 2373 428 1.38e+02 0.3224299 0.0581542 GO:0031325 GO:BP positive regulation of cellular metabolic process 13587 7551 GO:0009893, GO:0031323, GO:0044237, GO:0048522
query_1 TRUE 0.0000000 1249 428 9.00e+01 0.2102804 0.0720576 GO:0031327 GO:BP negative regulation of cellular biosynthetic process 13587 7553 GO:0009890, GO:0031324, GO:0031326, GO:0044249
query_1 TRUE 0.0000000 2425 428 1.40e+02 0.3271028 0.0577320 GO:0051173 GO:BP positive regulation of nitrogen compound metabolic process 13587 14401 GO:0006807, GO:0009893, GO:0051171
query_1 TRUE 0.0000000 1273 428 9.00e+01 0.2102804 0.0706991 GO:0009890 GO:BP negative regulation of biosynthetic process 13587 3844 GO:0009058, GO:0009889, GO:0009892
query_1 TRUE 0.0000000 2648 428 1.47e+02 0.3434579 0.0555136 GO:0010604 GO:BP positive regulation of macromolecule metabolic process 13587 4369 GO:0009893, GO:0043170, GO:0060255
query_1 TRUE 0.0000000 8501 428 3.36e+02 0.7850467 0.0395248 GO:0008152 GO:BP metabolic process 13587 3213 GO:0008150
query_1 TRUE 0.0000000 2306 428 1.30e+02 0.3037383 0.0563747 GO:0009892 GO:BP negative regulation of metabolic process 13587 3846 GO:0008152, GO:0019222, GO:0048519
query_1 TRUE 0.0000000 1866 428 1.12e+02 0.2616822 0.0600214 GO:0051172 GO:BP negative regulation of nitrogen compound metabolic process 13587 14400 GO:0006807, GO:0009892, GO:0051171
query_1 TRUE 0.0000000 2146 428 1.23e+02 0.2873832 0.0573159 GO:0010605 GO:BP negative regulation of macromolecule metabolic process 13587 4370 GO:0009892, GO:0043170, GO:0060255
query_1 TRUE 0.0000000 2884 428 1.49e+02 0.3481308 0.0516644 GO:0009893 GO:BP positive regulation of metabolic process 13587 3847 GO:0008152, GO:0019222, GO:0048518
query_1 TRUE 0.0000000 3628 428 1.75e+02 0.4088785 0.0482359 GO:0048523 GO:BP negative regulation of cellular process 13587 13627 GO:0009987, GO:0048519, GO:0050794
query_1 TRUE 0.0000000 4035 428 1.87e+02 0.4369159 0.0463445 GO:0048519 GO:BP negative regulation of biological process 13587 13623 GO:0008150, GO:0050789
query_1 TRUE 0.0000001 536 428 4.50e+01 0.1051402 0.0839552 GO:0006325 GO:BP chromatin organization 13587 2182 GO:0016043
query_1 TRUE 0.0000027 309 428 3.00e+01 0.0700935 0.0970874 GO:0006338 GO:BP chromatin remodeling 13587 2186 GO:0006325
query_1 TRUE 0.0000562 4148 428 1.77e+02 0.4135514 0.0426712 GO:0048522 GO:BP positive regulation of cellular process 13587 13626 GO:0009987, GO:0048518, GO:0050794
query_1 TRUE 0.0001845 4577 428 1.89e+02 0.4415888 0.0412934 GO:0048518 GO:BP positive regulation of biological process 13587 13622 GO:0008150, GO:0050789
query_1 TRUE 0.0002647 424 428 3.20e+01 0.0747664 0.0754717 GO:0016570 GO:BP histone modification 13587 5415 GO:0036211
query_1 TRUE 0.0011631 12 428 5.00e+00 0.0116822 0.4166667 GO:0010452 GO:BP histone H3-K36 methylation 13587 4257 GO:0034968
query_1 TRUE 0.0013697 1829 428 8.80e+01 0.2056075 0.0481137 GO:0050793 GO:BP regulation of developmental process 13587 14090 GO:0032502, GO:0050789
query_1 TRUE 0.0013866 120 428 1.40e+01 0.0327103 0.1166667 GO:0018022 GO:BP peptidyl-lysine methylation 13587 5494 GO:0006479, GO:0018205
query_1 TRUE 0.0015606 224 428 2.00e+01 0.0467290 0.0892857 GO:0006354 GO:BP DNA-templated transcription elongation 13587 2192 GO:0006351, GO:0032774
query_1 TRUE 0.0017063 107 428 1.30e+01 0.0303738 0.1214953 GO:0034968 GO:BP histone lysine methylation 13587 9262 GO:0016571, GO:0018022
query_1 TRUE 0.0020798 141 428 1.50e+01 0.0350467 0.1063830 GO:0016571 GO:BP histone methylation 13587 5416 GO:0006479, GO:0016570
query_1 TRUE 0.0055369 367 428 2.60e+01 0.0607477 0.0708447 GO:0018205 GO:BP peptidyl-lysine modification 13587 5601 GO:0018193
query_1 TRUE 0.0064837 4 428 3.00e+00 0.0070093 0.7500000 GO:0097676 GO:BP histone H3-K36 dimethylation 13587 19904 GO:0010452, GO:0018027
query_1 TRUE 0.0083303 178 428 1.60e+01 0.0373832 0.0898876 GO:0006479 GO:BP protein methylation 13587 2280 GO:0008213, GO:0043414
query_1 TRUE 0.0083303 178 428 1.60e+01 0.0373832 0.0898876 GO:0008213 GO:BP protein alkylation 13587 3228 GO:0036211
query_1 TRUE 0.0083303 789 428 4.40e+01 0.1028037 0.0557668 GO:0006974 GO:BP cellular response to DNA damage stimulus 13587 2675 GO:0033554
query_1 TRUE 0.0094433 18 428 5.00e+00 0.0116822 0.2777778 GO:0006607 GO:BP NLS-bearing protein import into nucleus 13587 2391 GO:0006606
query_1 TRUE 0.0099108 845 428 4.60e+01 0.1074766 0.0544379 GO:0060429 GO:BP epithelium development 13587 15559 GO:0009888
query_1 TRUE 0.0110510 657 428 3.80e+01 0.0887850 0.0578387 GO:0016071 GO:BP mRNA metabolic process 13587 5255 GO:0016070
query_1 TRUE 0.0147308 84 428 1.00e+01 0.0233645 0.1190476 GO:0045814 GO:BP negative regulation of gene expression, epigenetic 13587 12410 GO:0010629, GO:0040029
query_1 TRUE 0.0151756 227 428 1.80e+01 0.0420561 0.0792952 GO:0030522 GO:BP intracellular receptor signaling pathway 13587 7237 GO:0007165
query_1 TRUE 0.0227542 879 428 4.60e+01 0.1074766 0.0523322 GO:0072359 GO:BP circulatory system development 13587 18474 GO:0048731
query_1 TRUE 0.0231340 177 428 1.50e+01 0.0350467 0.0847458 GO:0090596 GO:BP sensory organ morphogenesis 13587 19524 GO:0007423, GO:0009887
query_1 TRUE 0.0235158 277 428 2.00e+01 0.0467290 0.0722022 GO:1903706 GO:BP regulation of hemopoiesis 13587 24477 GO:0002682, GO:0030097, GO:0060284, GO:2000026
query_1 TRUE 0.0235158 197 428 1.60e+01 0.0373832 0.0812183 GO:1902105 GO:BP regulation of leukocyte differentiation 13587 23159 GO:0002521, GO:1903706
query_1 TRUE 0.0235158 74 428 9.00e+00 0.0210280 0.1216216 GO:2000736 GO:BP regulation of stem cell differentiation 13587 27440 GO:0045595, GO:0048863
query_1 TRUE 0.0235158 141 428 1.30e+01 0.0303738 0.0921986 GO:0040029 GO:BP epigenetic regulation of gene expression 13587 10536 GO:0006325, GO:0010468
query_1 TRUE 0.0263267 6 428 3.00e+00 0.0070093 0.5000000 GO:0086023 GO:BP adenylate cyclase-activating adrenergic receptor signaling pathway involved in heart process 13587 19024 GO:0071880, GO:0086103
query_1 TRUE 0.0278172 76 428 9.00e+00 0.0210280 0.1184211 GO:0031507 GO:BP heterochromatin formation 13587 7631 GO:0045814, GO:0070828
query_1 TRUE 0.0306558 164 428 1.40e+01 0.0327103 0.0853659 GO:0007623 GO:BP circadian rhythm 13587 3168 GO:0048511
query_1 TRUE 0.0318091 531 428 3.10e+01 0.0724299 0.0583804 GO:0043009 GO:BP chordate embryonic development 13587 11117 GO:0009792
query_1 TRUE 0.0360655 36 428 6.00e+00 0.0140187 0.1666667 GO:1902275 GO:BP regulation of chromatin organization 13587 23312 GO:0006325, GO:0051128
query_1 TRUE 0.0398125 150 428 1.30e+01 0.0303738 0.0866667 GO:0019827 GO:BP stem cell population maintenance 13587 6416 GO:0032501, GO:0098727
query_1 TRUE 0.0417637 7 428 3.00e+00 0.0070093 0.4285714 GO:1900246 GO:BP positive regulation of RIG-I signaling pathway 13587 21551 GO:0039529, GO:0039535, GO:0062208
query_1 TRUE 0.0417637 2 428 2.00e+00 0.0046729 1.0000000 GO:0032242 GO:BP regulation of nucleoside transport 13587 7889 GO:0015858, GO:0032239
query_1 TRUE 0.0417637 2 428 2.00e+00 0.0046729 1.0000000 GO:1901898 GO:BP negative regulation of relaxation of cardiac muscle 13587 22972 GO:0055119, GO:1901078, GO:1901897
query_1 TRUE 0.0420232 15 428 4.00e+00 0.0093458 0.2666667 GO:0032239 GO:BP regulation of nucleobase-containing compound transport 13587 7886 GO:0015931, GO:0051049
query_1 TRUE 0.0429893 152 428 1.30e+01 0.0303738 0.0855263 GO:0098727 GO:BP maintenance of cell number 13587 20042 GO:0032502
query_1 TRUE 0.0468968 1415 428 6.50e+01 0.1518692 0.0459364 GO:0009888 GO:BP tissue development 13587 3842 GO:0048856
query_1 TRUE 0.0473282 154 428 1.30e+01 0.0303738 0.0844156 GO:0045165 GO:BP cell fate commitment 13587 12071 GO:0030154, GO:0048869
query_1 TRUE 0.0473282 83 428 9.00e+00 0.0210280 0.1084337 GO:0070828 GO:BP heterochromatin organization 13587 17383 GO:0006338
query_1 TRUE 0.0475458 501 428 2.90e+01 0.0677570 0.0578842 GO:0048729 GO:BP tissue morphogenesis 13587 13809 GO:0009653, GO:0009888
query_1 TRUE 0.0475458 234 428 1.70e+01 0.0397196 0.0726496 GO:0048511 GO:BP rhythmic process 13587 13617 GO:0008150
query_1 TRUE 0.0475458 548 428 3.10e+01 0.0724299 0.0565693 GO:0009792 GO:BP embryo development ending in birth or egg hatching 13587 3773 GO:0009790
query_1 TRUE 0.0477912 118 428 1.10e+01 0.0257009 0.0932203 GO:1902107 GO:BP positive regulation of leukocyte differentiation 13587 23161 GO:0002521, GO:1902105, GO:1903708
query_1 TRUE 0.0477912 118 428 1.10e+01 0.0257009 0.0932203 GO:1903708 GO:BP positive regulation of hemopoiesis 13587 24479 GO:0002684, GO:0010720, GO:0030097, GO:0051240, GO:1903706
query_1 TRUE 0.0477912 502 428 2.90e+01 0.0677570 0.0577689 GO:0007507 GO:BP heart development 13587 3080 GO:0048513, GO:0072359
query_1 TRUE 0.0481745 39 428 6.00e+00 0.0140187 0.1538462 GO:2001222 GO:BP regulation of neuron migration 13587 27870 GO:0001764, GO:0030334
query_1 TRUE 0.0481745 871 428 4.40e+01 0.1028037 0.0505166 GO:0009790 GO:BP embryo development 13587 3771 GO:0007275
query_1 TRUE 0.0000000 415 428 4.50e+01 0.1051402 0.1084337 KEGG:05168 KEGG Herpes simplex virus 1 infection 13587 442 KEGG:00000
source term_id term_name intersection_size term_size p_value
GO:BP GO:0006351 DNA-templated transcription 216 2683 4.83e-44
GO:BP GO:0097659 nucleic acid-templated transcription 216 2684 4.83e-44
GO:BP GO:0032774 RNA biosynthetic process 216 2714 1.67e-43
GO:BP GO:0006366 transcription by RNA polymerase II 183 1991 1.67e-43
GO:BP GO:1903506 regulation of nucleic acid-templated transcription 209 2581 6.11e-43
GO:BP GO:0019219 regulation of nucleobase-containing compound metabolic process 231 3105 6.11e-43
GO:BP GO:0006355 regulation of DNA-templated transcription 209 2579 6.11e-43
GO:BP GO:0006357 regulation of transcription by RNA polymerase II 178 1915 6.11e-43
GO:BP GO:2001141 regulation of RNA biosynthetic process 209 2598 1.31e-42
GO:BP GO:0051252 regulation of RNA metabolic process 219 2849 3.56e-42
GO:BP GO:0090304 nucleic acid metabolic process 260 4047 8.30e-39
GO:BP GO:0010556 regulation of macromolecule biosynthetic process 219 3015 4.49e-38
GO:BP GO:0016070 RNA metabolic process 241 3593 1.21e-37
GO:BP GO:0031323 regulation of cellular metabolic process 266 4305 4.72e-37
GO:BP GO:0034654 nucleobase-containing compound biosynthetic process 219 3083 1.48e-36
GO:BP GO:0031326 regulation of cellular biosynthetic process 220 3123 3.12e-36
GO:BP GO:0019438 aromatic compound biosynthetic process 220 3149 1.09e-35
GO:BP GO:0018130 heterocycle biosynthetic process 220 3148 1.09e-35
GO:BP GO:0009889 regulation of biosynthetic process 220 3174 3.81e-35
GO:BP GO:1901362 organic cyclic compound biosynthetic process 221 3253 5.63e-34
GO:BP GO:0010468 regulation of gene expression 233 3583 1.42e-33
GO:BP GO:0080090 regulation of primary metabolic process 263 4440 5.67e-33
GO:BP GO:0051171 regulation of nitrogen compound metabolic process 259 4330 6.53e-33
GO:BP GO:0009059 macromolecule biosynthetic process 236 3730 2.90e-32
GO:BP GO:0006139 nucleobase-containing compound metabolic process 263 4503 7.26e-32
GO:BP GO:0060255 regulation of macromolecule metabolic process 265 4640 1.81e-30
GO:BP GO:0046483 heterocycle metabolic process 264 4616 2.15e-30
GO:BP GO:0006725 cellular aromatic compound metabolic process 264 4646 6.97e-30
GO:BP GO:0044271 cellular nitrogen compound biosynthetic process 231 3758 3.33e-29
GO:BP GO:1901360 organic cyclic compound metabolic process 266 4790 1.86e-28
GO:BP GO:0010467 gene expression 258 4572 3.44e-28
GO:BP GO:0019222 regulation of metabolic process 273 5039 7.88e-28
GO:BP GO:0034641 cellular nitrogen compound metabolic process 268 4991 3.45e-26
GO:BP GO:0044249 cellular biosynthetic process 249 4465 1.14e-25
GO:BP GO:1901576 organic substance biosynthetic process 249 4537 1.61e-24
GO:BP GO:0009058 biosynthetic process 249 4595 1.28e-23
GO:BP GO:0043170 macromolecule metabolic process 322 7057 9.57e-22
GO:BP GO:0050794 regulation of cellular process 329 7579 2.78e-18
GO:BP GO:1903508 positive regulation of nucleic acid-templated transcription 105 1304 4.26e-18
GO:BP GO:0045893 positive regulation of DNA-templated transcription 105 1304 4.26e-18
GO:BP GO:0051254 positive regulation of RNA metabolic process 111 1431 4.68e-18
GO:BP GO:1902680 positive regulation of RNA biosynthetic process 105 1311 6.07e-18
GO:BP GO:0044237 cellular metabolic process 325 7503 1.55e-17
GO:BP GO:0045935 positive regulation of nucleobase-containing compound metabolic process 116 1600 1.05e-16
GO:BP GO:0006807 nitrogen compound metabolic process 321 7474 3.03e-16
GO:BP GO:0050789 regulation of biological process 335 7992 4.68e-16
GO:BP GO:0044238 primary metabolic process 329 7800 8.56e-16
GO:BP GO:0065007 biological regulation 344 8348 8.56e-16
GO:BP GO:0010557 positive regulation of macromolecule biosynthetic process 109 1499 1.23e-15
GO:BP GO:0045892 negative regulation of DNA-templated transcription 85 1009 2.00e-15
GO:BP GO:1903507 negative regulation of nucleic acid-templated transcription 85 1011 2.21e-15
GO:BP GO:1902679 negative regulation of RNA biosynthetic process 85 1020 3.73e-15
GO:BP GO:0045934 negative regulation of nucleobase-containing compound metabolic process 94 1215 7.17e-15
GO:BP GO:0051253 negative regulation of RNA metabolic process 89 1115 8.33e-15
GO:BP GO:0045944 positive regulation of transcription by RNA polymerase II 79 925 1.42e-14
GO:BP GO:0031328 positive regulation of cellular biosynthetic process 109 1571 3.23e-14
GO:BP GO:0071704 organic substance metabolic process 334 8150 5.29e-14
GO:BP GO:0009891 positive regulation of biosynthetic process 109 1598 1.04e-13
GO:BP GO:0031324 negative regulation of cellular metabolic process 116 1780 2.57e-13
GO:BP GO:0010558 negative regulation of macromolecule biosynthetic process 90 1206 3.13e-13
GO:BP GO:0000122 negative regulation of transcription by RNA polymerase II 65 735 1.83e-12
GO:BP GO:0031325 positive regulation of cellular metabolic process 138 2373 2.39e-12
GO:BP GO:0031327 negative regulation of cellular biosynthetic process 90 1249 2.44e-12
GO:BP GO:0051173 positive regulation of nitrogen compound metabolic process 140 2425 2.46e-12
GO:BP GO:0009890 negative regulation of biosynthetic process 90 1273 7.26e-12
GO:BP GO:0010604 positive regulation of macromolecule metabolic process 147 2648 1.02e-11
GO:BP GO:0008152 metabolic process 336 8501 3.09e-11
GO:BP GO:0009892 negative regulation of metabolic process 130 2306 1.80e-10
GO:BP GO:0051172 negative regulation of nitrogen compound metabolic process 112 1866 2.11e-10
GO:BP GO:0010605 negative regulation of macromolecule metabolic process 123 2146 2.90e-10
GO:BP GO:0009893 positive regulation of metabolic process 149 2884 2.01e-09
GO:BP GO:0048523 negative regulation of cellular process 175 3628 4.49e-09
GO:BP GO:0048519 negative regulation of biological process 187 4035 2.05e-08
GO:BP GO:0006325 chromatin organization 45 536 1.13e-07
GO:BP GO:0006338 chromatin remodeling 30 309 2.71e-06
GO:BP GO:0048522 positive regulation of cellular process 177 4148 5.62e-05
GO:BP GO:0048518 positive regulation of biological process 189 4577 1.85e-04
GO:BP GO:0016570 histone modification 32 424 2.65e-04
GO:BP GO:0010452 histone H3-K36 methylation 5 12 1.16e-03
GO:BP GO:0050793 regulation of developmental process 88 1829 1.37e-03
GO:BP GO:0018022 peptidyl-lysine methylation 14 120 1.39e-03
GO:BP GO:0006354 DNA-templated transcription elongation 20 224 1.56e-03
GO:BP GO:0034968 histone lysine methylation 13 107 1.71e-03
GO:BP GO:0016571 histone methylation 15 141 2.08e-03
GO:BP GO:0018205 peptidyl-lysine modification 26 367 5.54e-03
GO:BP GO:0097676 histone H3-K36 dimethylation 3 4 6.48e-03
GO:BP GO:0006479 protein methylation 16 178 8.33e-03
GO:BP GO:0008213 protein alkylation 16 178 8.33e-03
GO:BP GO:0006974 cellular response to DNA damage stimulus 44 789 8.33e-03
GO:BP GO:0006607 NLS-bearing protein import into nucleus 5 18 9.44e-03
GO:BP GO:0060429 epithelium development 46 845 9.91e-03
GO:BP GO:0016071 mRNA metabolic process 38 657 1.11e-02
GO:BP GO:0045814 negative regulation of gene expression, epigenetic 10 84 1.47e-02
GO:BP GO:0030522 intracellular receptor signaling pathway 18 227 1.52e-02
GO:BP GO:0072359 circulatory system development 46 879 2.28e-02
GO:BP GO:0090596 sensory organ morphogenesis 15 177 2.31e-02
GO:BP GO:1903706 regulation of hemopoiesis 20 277 2.35e-02
GO:BP GO:1902105 regulation of leukocyte differentiation 16 197 2.35e-02
GO:BP GO:2000736 regulation of stem cell differentiation 9 74 2.35e-02
GO:BP GO:0040029 epigenetic regulation of gene expression 13 141 2.35e-02
GO:BP GO:0086023 adenylate cyclase-activating adrenergic receptor signaling pathway involved in heart process 3 6 2.63e-02
GO:BP GO:0031507 heterochromatin formation 9 76 2.78e-02
GO:BP GO:0007623 circadian rhythm 14 164 3.07e-02
GO:BP GO:0043009 chordate embryonic development 31 531 3.18e-02
GO:BP GO:1902275 regulation of chromatin organization 6 36 3.61e-02
GO:BP GO:0019827 stem cell population maintenance 13 150 3.98e-02
GO:BP GO:1900246 positive regulation of RIG-I signaling pathway 3 7 4.18e-02
GO:BP GO:0032242 regulation of nucleoside transport 2 2 4.18e-02
GO:BP GO:1901898 negative regulation of relaxation of cardiac muscle 2 2 4.18e-02
GO:BP GO:0032239 regulation of nucleobase-containing compound transport 4 15 4.20e-02
GO:BP GO:0098727 maintenance of cell number 13 152 4.30e-02
GO:BP GO:0009888 tissue development 65 1415 4.69e-02
GO:BP GO:0045165 cell fate commitment 13 154 4.73e-02
GO:BP GO:0070828 heterochromatin organization 9 83 4.73e-02
GO:BP GO:0048729 tissue morphogenesis 29 501 4.75e-02
GO:BP GO:0048511 rhythmic process 17 234 4.75e-02
GO:BP GO:0009792 embryo development ending in birth or egg hatching 31 548 4.75e-02
GO:BP GO:1902107 positive regulation of leukocyte differentiation 11 118 4.78e-02
GO:BP GO:1903708 positive regulation of hemopoiesis 11 118 4.78e-02
GO:BP GO:0007507 heart development 29 502 4.78e-02
GO:BP GO:2001222 regulation of neuron migration 6 39 4.82e-02
GO:BP GO:0009790 embryo development 44 871 4.82e-02
KEGG KEGG:05168 Herpes simplex virus 1 infection 45 415 6.65e-11

Time-independent Top2\(\beta\) inhibitor motif genes

source term_id term_name intersection_size term_size p_value
GO:BP GO:0006357 regulation of transcription by RNA polymerase II 178 1915 4.27e-29
GO:BP GO:0006366 transcription by RNA polymerase II 180 1991 3.00e-28
GO:BP GO:0051252 regulation of RNA metabolic process 217 2849 2.60e-25
GO:BP GO:1903506 regulation of nucleic acid-templated transcription 204 2581 2.60e-25
GO:BP GO:0006355 regulation of DNA-templated transcription 204 2579 2.60e-25
GO:BP GO:2001141 regulation of RNA biosynthetic process 204 2598 4.68e-25
GO:BP GO:0097659 nucleic acid-templated transcription 206 2684 3.74e-24
GO:BP GO:0006351 DNA-templated transcription 206 2683 3.74e-24
GO:BP GO:0032774 RNA biosynthetic process 206 2714 1.52e-23
GO:BP GO:0019219 regulation of nucleobase-containing compound metabolic process 224 3105 2.64e-23
GO:BP GO:0010556 regulation of macromolecule biosynthetic process 213 3015 1.79e-20
GO:BP GO:0031326 regulation of cellular biosynthetic process 216 3123 1.09e-19
GO:BP GO:0090304 nucleic acid metabolic process 257 4047 1.14e-19
GO:BP GO:0009889 regulation of biosynthetic process 218 3174 1.29e-19
GO:BP GO:0034654 nucleobase-containing compound biosynthetic process 213 3083 2.52e-19
GO:BP GO:0010468 regulation of gene expression 235 3583 4.29e-19
GO:BP GO:0019438 aromatic compound biosynthetic process 215 3149 5.36e-19
GO:BP GO:0018130 heterocycle biosynthetic process 215 3148 5.36e-19
GO:BP GO:0016070 RNA metabolic process 235 3593 5.36e-19
GO:BP GO:1901362 organic cyclic compound biosynthetic process 217 3253 5.69e-18
GO:BP GO:0051171 regulation of nitrogen compound metabolic process 260 4330 1.50e-16
GO:BP GO:0080090 regulation of primary metabolic process 263 4440 5.17e-16
GO:BP GO:0060255 regulation of macromolecule metabolic process 271 4640 6.15e-16
GO:BP GO:0031323 regulation of cellular metabolic process 255 4305 3.04e-15
GO:BP GO:0006139 nucleobase-containing compound metabolic process 261 4503 1.65e-14
GO:BP GO:0046483 heterocycle metabolic process 264 4616 5.52e-14
GO:BP GO:0019222 regulation of metabolic process 281 5039 6.07e-14
GO:BP GO:0006725 cellular aromatic compound metabolic process 264 4646 1.27e-13
GO:BP GO:0009059 macromolecule biosynthetic process 225 3730 1.70e-13
GO:BP GO:0044271 cellular nitrogen compound biosynthetic process 225 3758 4.06e-13
GO:BP GO:0051253 negative regulation of RNA metabolic process 97 1115 7.31e-13
GO:BP GO:1901360 organic cyclic compound metabolic process 267 4790 8.90e-13
GO:BP GO:0010467 gene expression 256 4572 3.76e-12
GO:BP GO:0045892 negative regulation of DNA-templated transcription 89 1009 5.07e-12
GO:BP GO:1903507 negative regulation of nucleic acid-templated transcription 89 1011 5.53e-12
GO:BP GO:1902679 negative regulation of RNA biosynthetic process 89 1020 9.04e-12
GO:BP GO:0000122 negative regulation of transcription by RNA polymerase II 72 735 1.15e-11
GO:BP GO:0045934 negative regulation of nucleobase-containing compound metabolic process 99 1215 1.89e-11
GO:BP GO:0034641 cellular nitrogen compound metabolic process 270 4991 2.48e-11
GO:BP GO:0045944 positive regulation of transcription by RNA polymerase II 79 925 7.99e-10
GO:BP GO:0010558 negative regulation of macromolecule biosynthetic process 93 1206 2.62e-09
GO:BP GO:0031327 negative regulation of cellular biosynthetic process 95 1249 3.21e-09
GO:BP GO:0009890 negative regulation of biosynthetic process 96 1273 3.90e-09
GO:BP GO:0044249 cellular biosynthetic process 240 4465 5.35e-09
GO:BP GO:1901576 organic substance biosynthetic process 242 4537 9.24e-09
GO:BP GO:0050789 regulation of biological process 373 7992 1.06e-08
GO:BP GO:0009058 biosynthetic process 244 4595 1.10e-08
GO:BP GO:0043170 macromolecule metabolic process 339 7057 1.24e-08
GO:BP GO:0045893 positive regulation of DNA-templated transcription 95 1304 2.89e-08
GO:BP GO:1903508 positive regulation of nucleic acid-templated transcription 95 1304 2.89e-08
GO:BP GO:1902680 positive regulation of RNA biosynthetic process 95 1311 3.78e-08
GO:BP GO:0050794 regulation of cellular process 355 7579 6.74e-08
GO:BP GO:0051254 positive regulation of RNA metabolic process 99 1431 1.79e-07
GO:BP GO:0065007 biological regulation 380 8348 2.54e-07
GO:BP GO:0010557 positive regulation of macromolecule biosynthetic process 100 1499 9.63e-07
GO:BP GO:0031324 negative regulation of cellular metabolic process 113 1780 1.33e-06
GO:BP GO:0031328 positive regulation of cellular biosynthetic process 103 1571 1.33e-06
GO:BP GO:0009891 positive regulation of biosynthetic process 104 1598 1.60e-06
GO:BP GO:0045935 positive regulation of nucleobase-containing compound metabolic process 104 1600 1.68e-06
GO:BP GO:0031325 positive regulation of cellular metabolic process 139 2373 2.94e-06
GO:BP GO:0051173 positive regulation of nitrogen compound metabolic process 141 2425 3.53e-06
GO:BP GO:0010605 negative regulation of macromolecule metabolic process 127 2146 7.92e-06
GO:BP GO:0051172 negative regulation of nitrogen compound metabolic process 114 1866 8.40e-06
GO:BP GO:0010604 positive regulation of macromolecule metabolic process 149 2648 9.95e-06
GO:BP GO:0009893 positive regulation of metabolic process 159 2884 1.16e-05
GO:BP GO:0009892 negative regulation of metabolic process 133 2306 1.52e-05
GO:BP GO:0006807 nitrogen compound metabolic process 339 7474 3.21e-05
GO:BP GO:0044238 primary metabolic process 350 7800 4.85e-05
GO:BP GO:0071704 organic substance metabolic process 360 8150 1.64e-04
GO:BP GO:0003007 heart morphogenesis 23 212 4.45e-04
GO:BP GO:0044237 cellular metabolic process 334 7503 4.56e-04
GO:BP GO:0045595 regulation of cell differentiation 72 1134 7.05e-04
GO:BP GO:0048523 negative regulation of cellular process 180 3628 1.47e-03
GO:BP GO:0048645 animal organ formation 10 52 1.52e-03
GO:BP GO:0009952 anterior/posterior pattern specification 16 126 1.55e-03
GO:BP GO:0045597 positive regulation of cell differentiation 45 619 1.55e-03
GO:BP GO:0140467 integrated stress response signaling 8 34 2.11e-03
GO:BP GO:0060411 cardiac septum morphogenesis 11 67 2.67e-03
GO:BP GO:0008152 metabolic process 364 8501 5.44e-03
GO:BP GO:0060914 heart formation 7 30 6.77e-03
GO:BP GO:0007389 pattern specification process 26 305 6.79e-03
GO:BP GO:0035914 skeletal muscle cell differentiation 9 52 8.36e-03
GO:BP GO:0014706 striated muscle tissue development 20 210 9.46e-03
GO:BP GO:0051094 positive regulation of developmental process 59 958 9.56e-03
GO:BP GO:0045596 negative regulation of cell differentiation 35 478 9.88e-03
GO:BP GO:2000026 regulation of multicellular organismal development 61 1007 1.13e-02
GO:BP GO:0048738 cardiac muscle tissue development 19 198 1.19e-02
GO:BP GO:0021546 rhombomere development 3 4 1.24e-02
GO:BP GO:0048518 positive regulation of biological process 212 4577 1.37e-02
GO:BP GO:0060537 muscle tissue development 27 340 1.46e-02
GO:BP GO:0048519 negative regulation of biological process 190 4035 1.48e-02
GO:BP GO:0043009 chordate embryonic development 37 531 1.60e-02
GO:BP GO:0003002 regionalization 23 272 1.64e-02
GO:BP GO:0051726 regulation of cell cycle 57 950 2.16e-02
GO:BP GO:0001756 somitogenesis 8 48 2.22e-02
GO:BP GO:0051239 regulation of multicellular organismal process 105 2023 2.26e-02
GO:BP GO:0030336 negative regulation of cell migration 20 227 2.27e-02
GO:BP GO:0048522 positive regulation of cellular process 193 4148 2.34e-02
GO:BP GO:0002293 alpha-beta T cell differentiation involved in immune response 7 38 2.53e-02
GO:BP GO:0042093 T-helper cell differentiation 7 38 2.53e-02
GO:BP GO:0002287 alpha-beta T cell activation involved in immune response 7 38 2.53e-02
GO:BP GO:0002294 CD4-positive, alpha-beta T cell differentiation involved in immune response 7 38 2.53e-02
GO:BP GO:0035282 segmentation 10 75 2.59e-02
GO:BP GO:0009792 embryo development ending in birth or egg hatching 37 548 2.59e-02
GO:BP GO:0045598 regulation of fat cell differentiation 12 103 2.60e-02
GO:BP GO:0050793 regulation of developmental process 96 1829 2.61e-02
GO:BP GO:0048483 autonomic nervous system development 6 28 2.61e-02
GO:BP GO:1902893 regulation of miRNA transcription 8 51 2.98e-02
GO:BP GO:0007049 cell cycle 82 1522 3.18e-02
GO:BP GO:0060412 ventricular septum morphogenesis 7 40 3.20e-02
GO:BP GO:2000146 negative regulation of cell motility 20 236 3.20e-02
GO:BP GO:0002292 T cell differentiation involved in immune response 7 40 3.20e-02
GO:BP GO:0060429 epithelium development 51 845 3.20e-02
GO:BP GO:0051241 negative regulation of multicellular organismal process 46 741 3.21e-02
GO:BP GO:0061614 miRNA transcription 8 52 3.21e-02
GO:BP GO:0051093 negative regulation of developmental process 42 659 3.22e-02
GO:BP GO:0055017 cardiac muscle tissue growth 9 65 3.28e-02
GO:BP GO:0060284 regulation of cell development 39 600 3.37e-02
GO:BP GO:0048486 parasympathetic nervous system development 4 12 3.42e-02
GO:BP GO:0048729 tissue morphogenesis 34 501 3.42e-02
GO:BP GO:0045444 fat cell differentiation 17 187 3.42e-02
GO:BP GO:0007507 heart development 34 502 3.48e-02
GO:BP GO:0003151 outflow tract morphogenesis 9 66 3.50e-02
GO:BP GO:0003206 cardiac chamber morphogenesis 12 109 3.68e-02
GO:BP GO:0043954 cellular component maintenance 8 54 3.78e-02
GO:BP GO:0060562 epithelial tube morphogenesis 22 277 3.78e-02
GO:BP GO:0003197 endocardial cushion development 7 42 3.81e-02
GO:BP GO:0042127 regulation of cell population proliferation 64 1141 4.12e-02
GO:BP GO:0060840 artery development 10 82 4.25e-02
GO:BP GO:1900744 regulation of p38MAPK cascade 6 32 4.55e-02
GO:BP GO:0003281 ventricular septum development 9 69 4.55e-02
GO:BP GO:0010628 positive regulation of gene expression 47 781 4.71e-02
GO:BP GO:0040013 negative regulation of locomotion 21 265 4.78e-02
GO:BP GO:0060038 cardiac muscle cell proliferation 7 44 4.80e-02
KEGG KEGG:05168 Herpes simplex virus 1 infection 47 415 3.76e-09
KEGG KEGG:04115 p53 signaling pathway 11 65 3.17e-03
KEGG KEGG:05217 Basal cell carcinoma 9 49 5.76e-03
KEGG KEGG:05224 Breast cancer 14 117 5.91e-03
KEGG KEGG:05225 Hepatocellular carcinoma 16 145 5.91e-03
KEGG KEGG:05226 Gastric cancer 13 117 1.76e-02
KEGG KEGG:05202 Transcriptional misregulation in cancer 13 128 3.52e-02

long go frame

###long go kegg break


sessionInfo()
R version 4.2.2 (2022-10-31 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19044)

Matrix products: default

locale:
[1] LC_COLLATE=English_United States.utf8 
[2] LC_CTYPE=English_United States.utf8   
[3] LC_MONETARY=English_United States.utf8
[4] LC_NUMERIC=C                          
[5] LC_TIME=English_United States.utf8    

attached base packages:
[1] grid      stats     graphics  grDevices utils     datasets  methods  
[8] base     

other attached packages:
 [1] RColorBrewer_1.1-3  Cormotif_1.42.0     limma_3.52.4       
 [4] affy_1.74.0         Biobase_2.56.0      ggVennDiagram_1.2.2
 [7] scales_1.2.1        kableExtra_1.3.4    VennDiagram_1.7.3  
[10] futile.logger_1.4.3 gridExtra_2.3       BiocGenerics_0.42.0
[13] gprofiler2_0.2.1    lubridate_1.9.2     forcats_1.0.0      
[16] stringr_1.5.0       dplyr_1.1.0         purrr_1.0.1        
[19] readr_2.1.4         tidyr_1.3.0         tibble_3.1.8       
[22] ggplot2_3.4.1       tidyverse_2.0.0     workflowr_1.7.0    

loaded via a namespace (and not attached):
 [1] fs_1.6.1              webshot_0.5.4         httr_1.4.5           
 [4] rprojroot_2.0.3       tools_4.2.2           bslib_0.4.2          
 [7] utf8_1.2.3            R6_2.5.1              affyio_1.66.0        
[10] lazyeval_0.2.2        colorspace_2.1-0      withr_2.5.0          
[13] tidyselect_1.2.0      processx_3.8.0        compiler_4.2.2       
[16] git2r_0.31.0          preprocessCore_1.58.0 cli_3.6.0            
[19] rvest_1.0.3           formatR_1.14          xml2_1.3.3           
[22] plotly_4.10.1         labeling_0.4.2        sass_0.4.5           
[25] callr_3.7.3           systemfonts_1.0.4     digest_0.6.31        
[28] rmarkdown_2.20        svglite_2.1.1         pkgconfig_2.0.3      
[31] htmltools_0.5.4       fastmap_1.1.1         highr_0.10           
[34] htmlwidgets_1.6.1     rlang_1.0.6           rstudioapi_0.14      
[37] shiny_1.7.4           farver_2.1.1          jquerylib_0.1.4      
[40] generics_0.1.3        jsonlite_1.8.4        crosstalk_1.2.0      
[43] magrittr_2.0.3        Rcpp_1.0.10           munsell_0.5.0        
[46] fansi_1.0.4           lifecycle_1.0.3       stringi_1.7.12       
[49] whisker_0.4.1         yaml_2.3.7            zlibbioc_1.42.0      
[52] promises_1.2.0.1      hms_1.1.2             knitr_1.42           
[55] ps_1.7.2              pillar_1.8.1          futile.options_1.0.1 
[58] glue_1.6.2            evaluate_0.20         getPass_0.2-2        
[61] lambda.r_1.2.4        data.table_1.14.8     BiocManager_1.30.20  
[64] vctrs_0.5.2           tzdb_0.3.0            httpuv_1.6.9         
[67] gtable_0.3.1          cachem_1.0.7          xfun_0.37            
[70] mime_0.12             xtable_1.8-4          later_1.3.0          
[73] RVenn_1.1.0           viridisLite_0.4.1     timechange_0.2.0     
[76] ellipsis_0.3.2