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  • watermark
    Member
    • Nov 2013
    • 20

    #1

    Which kind of microRNA expression are measured in TCGA?

    Hi all,

    I have download the mRNA and microRNA NGS data from TCGA for BRCA.
    for downloading the microRNA data, I choosed the miRNASeq from filter setting.
    Now I have the expression level of miRNA in diffrent samples.
    The question for is that, which kind of microRNA they are quantified ? is it all mature miRNA ? or mirna precursor are also there ? They seqenced miRNA which they got from gel electrophoresis ?(to be sure that, all of them have same length in case of mature miRNA).
    But when I look at the miRNA IDs; there is some problem:
    for example : they have expression level for hsa-mir-135a-2 , which when I search for it in miRBase, it's stem loop and it's mature form in miRbase is hsa-miR-135a-5p . so now I'm really in trouble to undersrand that expression level of which type of miRNA are quantified ?

    would someone clarify it more ?
  • GenePool
    Registered Vendor
    • Mar 2014
    • 18

    #2
    If you look at the "DESCRIPTION.TXT" files included in each package, there is the following description:

    This data archive contains the miRNA expression data for cancer samples
    of The Cancer Genome Atlas (TCGA) project. The experiments were
    performed by the BCCA Genome Sciences Centre in BC using the miRNA-Seq approach
    on the Illumina platform.

    Please see DESCRIPTION.txt in the mage-tab for algorithm description of the data protocols.

    The .adf file format describing miRNA annotations is as follows:

    MiRNA ID
    miRBase version
    genome version and coordinates as <version>:<Chromosome>:<Start position>-<End position>:<Strand>
    precursor sequence
    mature strand coordinates relative to precursor coordinates, as <relative start>-<relative end>
    mature strand accession
    alternate mature strand coordinates, if provided by miRBase
    alternate mature form accession
    star strand name, if provided by miRBase
    star strand form accession

    The .mirna.quantification.txt data file describing summed expression for each miRNA is as follows:

    miRNA name
    raw read count
    reads per million miRNA reads
    cross-mapped to other miRNA forms (Y or N)

    The .isoform.quantification.txt data file describing every individual sequence isoform observed is as follows:

    miRNA name
    alignment coordinates as <version>:<Chromosome>:<Start position>-<End position>:<Strand>
    raw read count
    reads per million miRNA reads
    cross-mapped to other miRNA forms (Y or N)
    region within miRNA

    ------------------

    When one looks at the associated files such as *.isoform.quantification.txt and *.mirna.quantification.txt, one can get a sense of the coordinates for which counts were calculated.

    As an example, let's take a look at "hsa-let-7a-1" below. You'll notice that the mature and star forms are mentioned in the last column. If you look at column two, you'll see that the reads all align to a range of 25 nucleotides (hg19:9:96938242-96938267:+) for the mature miRNA of hsa-let-7a-1 and a range of 25 nucleotides (hg19:9:96938292-96938317:+) for the star miRNA of hsa-let-7a-1.

    From *.isoform.quantification.txt for one sample:

    hsa-let-7a-1 hg19:9:96938242-96938264:+ 4 1.495846 N mature,MIMAT0000062
    hsa-let-7a-1 hg19:9:96938242-96938266:+ 4 1.495846 N mature,MIMAT0000062
    hsa-let-7a-1 hg19:9:96938243-96938264:+ 8 2.991692 N mature,MIMAT0000062
    hsa-let-7a-1 hg19:9:96938243-96938265:+ 4 1.495846 N mature,MIMAT0000062
    hsa-let-7a-1 hg19:9:96938243-96938266:+ 6 2.243769 N mature,MIMAT0000062
    hsa-let-7a-1 hg19:9:96938244-96938263:+ 157 58.711957 N mature,MIMAT0000062
    hsa-let-7a-1 hg19:9:96938244-96938264:+ 5196 1943.104000 N mature,MIMAT0000062
    hsa-let-7a-1 hg19:9:96938244-96938265:+ 3954 1478.643806 N mature,MIMAT0000062
    hsa-let-7a-1 hg19:9:96938244-96938266:+ 7029 2628.575446 N mature,MIMAT0000062
    hsa-let-7a-1 hg19:9:96938244-96938267:+ 278 103.961299 N mature,MIMAT0000062
    hsa-let-7a-1 hg19:9:96938244-96938268:+ 18 6.731307 N mature,MIMAT0000062
    hsa-let-7a-1 hg19:9:96938245-96938264:+ 9 3.365654 N mature,MIMAT0000062
    hsa-let-7a-1 hg19:9:96938245-96938265:+ 16 5.983384 N mature,MIMAT0000062
    hsa-let-7a-1 hg19:9:96938245-96938266:+ 44 16.454306 N mature,MIMAT0000062
    hsa-let-7a-1 hg19:9:96938245-96938267:+ 3 1.121885 N mature,MIMAT0000062
    hsa-let-7a-1 hg19:9:96938246-96938264:+ 1 0.373962 N mature,MIMAT0000062
    hsa-let-7a-1 hg19:9:96938247-96938265:+ 2 0.747923 N mature,MIMAT0000062
    hsa-let-7a-1 hg19:9:96938247-96938266:+ 10 3.739615 N mature,MIMAT0000062
    hsa-let-7a-1 hg19:9:96938247-96938267:+ 2 0.747923 N mature,MIMAT0000062
    hsa-let-7a-1 hg19:9:96938248-96938266:+ 1 0.373962 N mature,MIMAT0000062
    hsa-let-7a-1 hg19:9:96938248-96938267:+ 2 0.747923 N mature,MIMAT0000062
    hsa-let-7a-1 hg19:9:96938292-96938311:+ 1 0.373962 N star,MIMAT0004481
    hsa-let-7a-1 hg19:9:96938295-96938314:+ 3 1.121885 N star,MIMAT0004481
    hsa-let-7a-1 hg19:9:96938295-96938315:+ 6 2.243769 N star,MIMAT0004481
    hsa-let-7a-1 hg19:9:96938295-96938316:+ 13 4.861500 N star,MIMAT0004481
    hsa-let-7a-1 hg19:9:96938295-96938317:+ 20 7.479230 N star,MIMAT0004481
    hsa-let-7a-1 hg19:9:96938296-96938316:+ 3 1.121885 N star,MIMAT0004481
    hsa-let-7a-1 hg19:9:96938296-96938317:+ 1 0.373962 N star,MIMAT0004481

    From *.mirna.quantification.txt for the same sample

    miRNA_ID read_count reads_per_million_miRNA_mapped cross-mapped
    hsa-let-7a-1 16795 6280.683542 N

    ==================

    The count of 16795 in *.mirna.quantification.txt for hsa-let-7a-1 is literally the sum of all the counts mapped to the 25-nucleotide-ranges for the mature and star regions of hsa-let-7a-1.

    So in conclusion, the values represent expression for the mature miRNAs, not the stem loops.

    Incidentally, if you're interested, we have imported all of the miRNA-Seq data along with all of the other TCGA assays into GenePool and linked in all of the patient & sample metadata. GenePool makes it very simple to slice and dice the samples according to patient characteristics and clinical metadata, then run analyses.

    Here are the links to related threads:

    Registered SEQanswers sponsors/vendors can post commercial content here. Please support our sponsors!

    Registered SEQanswers sponsors/vendors can post commercial content here. Please support our sponsors!


    Good Luck!

    ------------------------------
    GenePool is making genomics data management, analysis, and sharing easier!
    Products @ www.stationxinc.com
    Last edited by GenePool; 11-23-2014, 09:26 PM.

    Comment

    • LisaXiao
      Junior Member
      • Feb 2015
      • 1

      #3
      Hey

      Hey, this problem troubles me too. However, after I checked as what you said, it seemed that the values represent expression for the mature miRNAs, ADDING the stem loops and PRECURSOR.





      Originally posted by GenePool View Post
      If you look at the "DESCRIPTION.TXT" files included in each package, there is the following description:

      This data archive contains the miRNA expression data for cancer samples
      of The Cancer Genome Atlas (TCGA) project. The experiments were
      performed by the BCCA Genome Sciences Centre in BC using the miRNA-Seq approach
      on the Illumina platform.

      Please see DESCRIPTION.txt in the mage-tab for algorithm description of the data protocols.

      The .adf file format describing miRNA annotations is as follows:

      MiRNA ID
      miRBase version
      genome version and coordinates as <version>:<Chromosome>:<Start position>-<End position>:<Strand>
      precursor sequence
      mature strand coordinates relative to precursor coordinates, as <relative start>-<relative end>
      mature strand accession
      alternate mature strand coordinates, if provided by miRBase
      alternate mature form accession
      star strand name, if provided by miRBase
      star strand form accession

      The .mirna.quantification.txt data file describing summed expression for each miRNA is as follows:

      miRNA name
      raw read count
      reads per million miRNA reads
      cross-mapped to other miRNA forms (Y or N)

      The .isoform.quantification.txt data file describing every individual sequence isoform observed is as follows:

      miRNA name
      alignment coordinates as <version>:<Chromosome>:<Start position>-<End position>:<Strand>
      raw read count
      reads per million miRNA reads
      cross-mapped to other miRNA forms (Y or N)
      region within miRNA

      ------------------

      When one looks at the associated files such as *.isoform.quantification.txt and *.mirna.quantification.txt, one can get a sense of the coordinates for which counts were calculated.

      As an example, let's take a look at "hsa-let-7a-1" below. You'll notice that the mature and star forms are mentioned in the last column. If you look at column two, you'll see that the reads all align to a range of 25 nucleotides (hg19:9:96938242-96938267:+) for the mature miRNA of hsa-let-7a-1 and a range of 25 nucleotides (hg19:9:96938292-96938317:+) for the star miRNA of hsa-let-7a-1.

      From *.isoform.quantification.txt for one sample:

      hsa-let-7a-1 hg19:9:96938242-96938264:+ 4 1.495846 N mature,MIMAT0000062
      hsa-let-7a-1 hg19:9:96938242-96938266:+ 4 1.495846 N mature,MIMAT0000062
      hsa-let-7a-1 hg19:9:96938243-96938264:+ 8 2.991692 N mature,MIMAT0000062
      hsa-let-7a-1 hg19:9:96938243-96938265:+ 4 1.495846 N mature,MIMAT0000062
      hsa-let-7a-1 hg19:9:96938243-96938266:+ 6 2.243769 N mature,MIMAT0000062
      hsa-let-7a-1 hg19:9:96938244-96938263:+ 157 58.711957 N mature,MIMAT0000062
      hsa-let-7a-1 hg19:9:96938244-96938264:+ 5196 1943.104000 N mature,MIMAT0000062
      hsa-let-7a-1 hg19:9:96938244-96938265:+ 3954 1478.643806 N mature,MIMAT0000062
      hsa-let-7a-1 hg19:9:96938244-96938266:+ 7029 2628.575446 N mature,MIMAT0000062
      hsa-let-7a-1 hg19:9:96938244-96938267:+ 278 103.961299 N mature,MIMAT0000062
      hsa-let-7a-1 hg19:9:96938244-96938268:+ 18 6.731307 N mature,MIMAT0000062
      hsa-let-7a-1 hg19:9:96938245-96938264:+ 9 3.365654 N mature,MIMAT0000062
      hsa-let-7a-1 hg19:9:96938245-96938265:+ 16 5.983384 N mature,MIMAT0000062
      hsa-let-7a-1 hg19:9:96938245-96938266:+ 44 16.454306 N mature,MIMAT0000062
      hsa-let-7a-1 hg19:9:96938245-96938267:+ 3 1.121885 N mature,MIMAT0000062
      hsa-let-7a-1 hg19:9:96938246-96938264:+ 1 0.373962 N mature,MIMAT0000062
      hsa-let-7a-1 hg19:9:96938247-96938265:+ 2 0.747923 N mature,MIMAT0000062
      hsa-let-7a-1 hg19:9:96938247-96938266:+ 10 3.739615 N mature,MIMAT0000062
      hsa-let-7a-1 hg19:9:96938247-96938267:+ 2 0.747923 N mature,MIMAT0000062
      hsa-let-7a-1 hg19:9:96938248-96938266:+ 1 0.373962 N mature,MIMAT0000062
      hsa-let-7a-1 hg19:9:96938248-96938267:+ 2 0.747923 N mature,MIMAT0000062
      hsa-let-7a-1 hg19:9:96938292-96938311:+ 1 0.373962 N star,MIMAT0004481
      hsa-let-7a-1 hg19:9:96938295-96938314:+ 3 1.121885 N star,MIMAT0004481
      hsa-let-7a-1 hg19:9:96938295-96938315:+ 6 2.243769 N star,MIMAT0004481
      hsa-let-7a-1 hg19:9:96938295-96938316:+ 13 4.861500 N star,MIMAT0004481
      hsa-let-7a-1 hg19:9:96938295-96938317:+ 20 7.479230 N star,MIMAT0004481
      hsa-let-7a-1 hg19:9:96938296-96938316:+ 3 1.121885 N star,MIMAT0004481
      hsa-let-7a-1 hg19:9:96938296-96938317:+ 1 0.373962 N star,MIMAT0004481

      From *.mirna.quantification.txt for the same sample

      miRNA_ID read_count reads_per_million_miRNA_mapped cross-mapped
      hsa-let-7a-1 16795 6280.683542 N

      ==================

      The count of 16795 in *.mirna.quantification.txt for hsa-let-7a-1 is literally the sum of all the counts mapped to the 25-nucleotide-ranges for the mature and star regions of hsa-let-7a-1.

      So in conclusion, the values represent expression for the mature miRNAs, not the stem loops.

      Incidentally, if you're interested, we have imported all of the miRNA-Seq data along with all of the other TCGA assays into GenePool and linked in all of the patient & sample metadata. GenePool makes it very simple to slice and dice the samples according to patient characteristics and clinical metadata, then run analyses.

      Here are the links to related threads:

      Registered SEQanswers sponsors/vendors can post commercial content here. Please support our sponsors!

      Registered SEQanswers sponsors/vendors can post commercial content here. Please support our sponsors!


      Good Luck!

      ------------------------------
      GenePool is making genomics data management, analysis, and sharing easier!
      Products @ www.stationxinc.com
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