R/Module_3.R

In drmonaco/AVARDA: AntiViral Antibody Response Deconvolution Algorithm (AVARDA), a multi-module software package for analyzing VirScan datasets

#' @export
#' @import igraph
#' @import progress

Module_3 = function(mod1,mod2,blast,total_prob,pairwise,dict,mod_3 = "run"){
mod2 = mod2 %>% arrange(pVal_f) %>% select(virus) %>% unlist %>% as.character()
mod1 = mod1[[3]] %>% select(1,mod2)
df = list()
R1 = 2
key.R = 1
while(R1<=dim(mod1)[2]){
  #print(dim(mod1)[2])
  # print(c("R1_",R1))
  # print("evaluating virus",key.R, "out of",length(mod2))
  vi = colnames(mod1)[R1]
  #print(vi)
  if(R1 == dim(mod1)[2] | mod_3 == "skip"){
    df[[key.R]] = mod1 %>% select(1,2)
    mod1 = mod1 %>% select(-vi)
  }
  if(R1 <= dim(mod1)[2] & mod_3 != "skip"){
  pb <- progress_bar$new(total = dim(mod1)[2])

  for(R2 in (R1+1):dim(mod1)[2]){
    pb$tick()
    comp = pairwise_comparator(mod1 %>% select(c(1,R1,R2)),pairwise,dict)
    if(comp[[1]]<.05 & comp[[2]]<.05){  #if both significant

    }
    if(comp[[1]]<.05 & comp[[2]]>.05){ # if v_i is significant
    #index = which(mod1[,..R1] > 0)
    index = which(mod1[,R1] > 0)
    mod1[index,R2] = 0
    }
    if(comp[[1]]>.05 & comp[[2]]<.05){ # if v_j is significant
    #index = which(mod1[,..R2] > 0)
    index = which(mod1[,R2] > 0)
    mod1[index,R1] = 0

    }
    if(comp[[1]]>.05 & comp[[2]]>.05){ # if neither is significant

    }
  }
  rest = rowSums(select(mod1,-1, -R1))
  case = mod1 %>% select(R1)
  df[[key.R]] = mod1 %>% select(1,2)
  mod1 = mod1 %>% filter(!(case > 0 & rest == 0)) %>% select(-vi)
  f = Module_2(x =mod1 ,dict = dict,total_prob = total_prob) %>% select(virus) %>% unlist() %>% as.character()
  mod1 = mod1 %>% select(c(V1,f))
  #R1 = R1+1
  }
  key.R = key.R +1
  }
return(df)
}