Tukukkk

I am new to R Programming and I am currently looking to analyse a huge dataset of genes. I am attempting to alter a nested loop that currently works to see which genes are up-regulated given varying adjusted P values and LogFC values to see the same but for down-regulated genes. What I have generated for the up-regulated genes is a 4x4 table looking to see how the number of genes that meet the cut off values I have selected for the P adjusted value and the LogFC varies. The image shows the coding used for the nested loop What I am getting when I attempt to execute this for the down-regulated genes is the same values - I am assuming R is not registering any changes and returns the same numbers.
Any advice would be much appreciated.

 #--------------------------------------------------------------------------------

# Function to calculate number of up regulated genes

#--------------------------------------------------------------------------------

get.upregulated.genes <- function(dafra, p.value.max, log.fc.min) {

  gene.count <- subset(dafra, adj.P.Val <= p.value.max & logFC >= log.fc.min) %>% 

    .[["Gene.symbol"]] %>% unique %>% length

  return(gene.count)

}



get.upregulated.genes(dafra=df3, p.value.max=0.05, log.fc.min=1) # 429



p.values <- c(0.001, 0.005, 0.01, 0.05)

log.fcs <- rev(c(0.5, 1, 1.5, 2))

log.fcs

mx.up <- matrix(rep(NA, 16), ncol=4)

mx.up

colnames(mx.up) <- p.values

rownames(mx.up) <- log.fcs



for (x in p.values) {

  for (y in log.fcs) {

    z <- get.upregulated.genes(df3, x, y)

    mx.up[as.character(y),as.character(x)] <- z

  }

}

mx.up

View(mx.up)



for (x in p.values) {

  for (y in log.fcs) {

    z <- get.upregulated.genes(df3, x, y)

    print(x)

    print(y)

    print(z)

    print("------")

  }

}

No need for forloops, try something like this (not tested, as there is no example data):

# get all combos

x <- expand.grid(

  p.values = c(0.001, 0.005, 0.01, 0.05),

  log.fcs = rev(c(0.5, 1, 1.5, 2)))



# loop rowby then get length of unique genes

apply(x, 1, function(i){

  length(unique(df3[ df3$adj.P.Val <= i[ 1 ] & df3$logFC >= i[ 2 ], "Gene.symbol" ]))

  })