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  • osha84
    Junior Member
    • May 2013
    • 7

    #1

    One density plots for multiple samples

    Hello everyone,

    Basically I have done normalization on my microarry 450k data using Lumi package followed by BMIQ beta mixture quantile normalization. It was easy to generate some plots when I was using the lumi library because I was basically following the manual but as I finished BMIQ I found it really hard to generate the plots because it's a different package and doesn't have a manual.

    My file consist of 57 columns, first column is probes ID and the rest of the columns are beta values for each sample in my data, and about 12000 rows.

    I'm fairly new to R and coding on general so after following some of the online source i could generate one plot for only one sample and it gets complicated and tedious to do the same thing over 50 times.

    Can any one please help me writing this code so I can overlay multiple densities in one plot?

    It would be much appreciated.
  • TiborNagy
    Senior Member
    • Mar 2010
    • 329

    #2
    To draw into an existing canvas, you can use the following commands:
    lines(), points(), polygon(), box()

    Comment

    • osha84
      Junior Member
      • May 2013
      • 7

      #3
      Originally posted by TiborNagy View Post
      To draw into an existing canvas, you can use the following commands:
      lines(), points(), polygon(), box()
      I need more explanation please. I also have another issue! the error I keep getting is that argument X is not a numeric, so I used "as.numeric" function but it's not working properly. I followed some tutorials online but just failed to treat my data as numeric.

      Comment

      • TiborNagy
        Senior Member
        • Mar 2010
        • 329

        #4
        First of all, check your input data:
        Code:
        str(data)
        This command will show you the class of every column. If you find any discrepancy, fix it.
        Drawing more than one density:
        Code:
        plot(density(data$V1), xlim=c(min(data), max(data)), ylim=c(0,1))
        lines(density(data$V2))
        lines(density(data$V3))
        Or you can use sm.density.compare.

        Comment

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