Cormotifcluster_analysis

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Last updated: 2023-04-18

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Knit directory: Cardiotoxicity/

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Ignored files:
    Ignored:    .RData
    Ignored:    .Rhistory
    Ignored:    .Rproj.user/
    Ignored:    data/Clamp_Summary.csv
    Ignored:    data/Cormotif_24_k1-5_raw.RDS
    Ignored:    data/DAgostres24.RDS
    Ignored:    data/DAtable1.csv
    Ignored:    data/DDE_reQTL.txt
    Ignored:    data/DDEresp_list.csv
    Ignored:    data/DEG_cormotif.RDS
    Ignored:    data/DF_Plate_Peak.csv
    Ignored:    data/Da24counts.txt
    Ignored:    data/Dx24counts.txt
    Ignored:    data/Dx_reQTL_specific.txt
    Ignored:    data/Ep24counts.txt
    Ignored:    data/GOplots.R
    Ignored:    data/K_cluster
    Ignored:    data/K_cluster_kisthree.csv
    Ignored:    data/K_cluster_kistwo.csv
    Ignored:    data/Mt24counts.txt
    Ignored:    data/RINsamplelist.txt
    Ignored:    data/Seonane2019supp1.txt
    Ignored:    data/TOP2Bi-24hoursGO_analysis.csv
    Ignored:    data/TR24counts.txt
    Ignored:    data/Top2biresp_cluster24h.csv
    Ignored:    data/Viabilitylistfull.csv
    Ignored:    data/allexpressedgenes.txt
    Ignored:    data/allgenes.txt
    Ignored:    data/allmatrix.RDS
    Ignored:    data/avgLD50.RDS
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    Ignored:    data/cormotif_3hk1-8.RDS
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    Ignored:    data/cormotif_initialall.RDS
    Ignored:    data/counts24hours.RDS
    Ignored:    data/cpmnorm_counts.csv
    Ignored:    data/dat_cpm.RDS
    Ignored:    data/data_outline.txt
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    Ignored:    data/efit2results.RDS
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    Ignored:    data/gostresTop2bi_LR
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    Ignored:    data/individualDRCfile.RDS
    Ignored:    data/knowles56.GMT
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    Ignored:    data/venn_code.R

Untracked files:
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    Untracked:  .RDataTmp1
    Untracked:  .RDataTmp2
    Untracked:  analysis/other_analysis.Rmd
    Untracked:  code/extra_code.R
    Untracked:  cormotif_probability_genelist.csv
    Untracked:  output/figure_1.Rmd
    Untracked:  output/output-old/
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    Untracked:  output/sequencing_info.txt
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    Untracked:  output/tabletop2Bi_ER.csv
    Untracked:  output/tabletop2Bi_LR.csv
    Untracked:  output/tabletop2Bi_TI.csv
    Untracked:  output/toplistall.csv
    Untracked:  reneebasecode.R

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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---

These are the previous versions of the repository in which changes were made to the R Markdown (analysis/Cormotifcluster_analysis.Rmd) and HTML (docs/Cormotifcluster_analysis.html) files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view the files as they were in that past version.

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

Session information

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