Announcement

Collapse
No announcement yet.
X
 
  • Filter
  • Time
  • Show
Clear All
new posts

  • RPKM calculation help

    I am trying to write a PERL script to calculate the RPKM for genes of interest and I need some verification that I am doing this calculation correctly. There are 31.8 million mapped reads on the genome.

    Here is the GFF3 file of a gene for example. There are 4,011 reads that map to this gene (between positions 4542759 and 4544980).

    Chr2 MSU_osa1r6 gene 4542759 4544980 . + . ID=13102.t00754;Name=unknown gene
    Chr2 MSU_osa1r6 mRNA 4542759 4544980 . + . ID=13102.m00974;Parent=13102.t00754
    Chr2 MSU_osa1r6 five_prime_UTR 4542759 4543030 . + . Parent=13102.m00974
    Chr2 MSU_osa1r6 CDS 4543031 4543177 . + 0 Parent=13102.m00974
    Chr2 MSU_osa1r6 CDS 4543287 4543709 . + 0 Parent=13102.m00974
    Chr2 MSU_osa1r6 CDS 4543836 4543952 . + 0 Parent=13102.m00974
    Chr2 MSU_osa1r6 CDS 4544064 4544423 . + 0 Parent=13102.m00974
    Chr2 MSU_osa1r6 three_prime_UTR 4544424 4544980 . + . Parent=13102.m00974

    There are 4 exons for this particular gene which contain a total of 1,043 base pairs.

    So the RPKM for this particular gene is ((4,011 reads/1.043kb of exon)/31.8mill mapped reads) = 120.9RPKM

    Is my calculation correct?

    Also, if there are reads that map to the intron regions or partial intron regions, should those reads be excluded from the calculation?
    This gene also has 3 other alternative spliced forms, which splicing is the correct one?

    Thanks in advance

  • #2
    Any comments anybody?

    Comment


    • #3
      I really need to know if this calculation is correct or not.
      Is there anybody out there that knows how to calculate RPKM?

      Comment


      • #4
        hi kwatts59,

        Your calculation seems to be correct.

        About the second question. You need to define the "trascriptional units". if your aim is to establish a "gene level" expression your trascriptional unit should be the full gene exons set. If you are interested in "isoforms level expression" you should calculate rpkm for each isoform.

        here you can find some examples:

        http://woldlab.caltech.edu/rnaseq/


        http://sandberg.cmb.ki.se/media/data/rnaseq/instructions-rpkmforgenes.html

        [
        URL="http://cufflinks.cbcb.umd.edu/"]
        http://cufflinks.cbcb.umd.edu/[/URL]



        cheers


        M.

        Comment


        • #5
          Yes, your calculation is correct, if you want to compute RPKM values according to the original definition suggested by Mortazavi et al. However, once you have alternative splicing, dividing by the sum of all exons, no matter whether they are used or not (or maybe even mutually exclusive), may cause severe problems and this is why Trapnell et al. (Nature Biotechnology 28: 511 (2010)) argued that the definition is not such a good one.

          On the other hand, it does not matter that much how you normalize for transcript length, because in most use cases, you won't be interested in absolute expression anyway, because you end up only comparing the expression of the same gene across samples rather than comparing expression between different genes.

          Comment

          Latest Articles

          Collapse

          • seqadmin
            Advanced Tools Transforming the Field of Cytogenomics
            by seqadmin


            At the intersection of cytogenetics and genomics lies the exciting field of cytogenomics. It focuses on studying chromosomes at a molecular scale, involving techniques that analyze either the whole genome or particular DNA sequences to examine variations in structure and behavior at the chromosomal or subchromosomal level. By integrating cytogenetic techniques with genomic analysis, researchers can effectively investigate chromosomal abnormalities related to diseases, particularly...
            09-26-2023, 06:26 AM
          • seqadmin
            How RNA-Seq is Transforming Cancer Studies
            by seqadmin



            Cancer research has been transformed through numerous molecular techniques, with RNA sequencing (RNA-seq) playing a crucial role in understanding the complexity of the disease. Maša Ivin, Ph.D., Scientific Writer at Lexogen, and Yvonne Goepel Ph.D., Product Manager at Lexogen, remarked that “The high-throughput nature of RNA-seq allows for rapid profiling and deep exploration of the transcriptome.” They emphasized its indispensable role in cancer research, aiding in biomarker...
            09-07-2023, 11:15 PM

          ad_right_rmr

          Collapse

          News

          Collapse

          Topics Statistics Last Post
          Started by seqadmin, 09-29-2023, 09:38 AM
          0 responses
          10 views
          0 likes
          Last Post seqadmin  
          Started by seqadmin, 09-27-2023, 06:57 AM
          0 responses
          13 views
          0 likes
          Last Post seqadmin  
          Started by seqadmin, 09-26-2023, 07:53 AM
          0 responses
          30 views
          0 likes
          Last Post seqadmin  
          Started by seqadmin, 09-25-2023, 07:42 AM
          0 responses
          18 views
          0 likes
          Last Post seqadmin  
          Working...
          X