Unconfigured Ad

Collapse
X
 
  • Time
  • Show
Clear All
new posts
  • vivekk
    Junior Member
    • Jan 2011
    • 3

    #1

    Cufflinks question

    Hi,

    I'm trying to set up a local version of Galaxy with all the NGS tools. I'm using this primarily for miRNA-seq data. So the workflow I'm using right now is:

    FASTQ Groomer > Clipper > Map w/ Bowtie for Illumina > Filter SAM (for mapped) > Sort SAM for Cufflinks > Cufflinks

    Now, this pipeline is working fine. I'm getting the 3 outputs from Cufflinks with FPKM etc. My question is this:

    Is there a way in Cufflinks to generate "sequence-level" RPKM output from the SAM file? For example:

    If I'm considering let-7a - my reads contain different versions/isoforms of different lengths:

    let-7a --- TGAGGTAGTAGGTTGTATAGTT --- "x" RPKM
    let-7a --- TGAGGTAGTAGGTTGTATAGT --- "y" RPKM
    let-7a --- TGAGGTAGTAGGTTGTATAGTTT --- "z" RPKM

    Can I get an output like the one above?
    When I run Cufflinks on my Bowtie mapped SAM file, I get the FPKM counts for the miRNAs where - either all the isoforms mapping to the same miRNA are combined or only the most abundant isoform is considered (I'm not sure which). In any case, no sequences are reported in the Cufflinks output.

    By the way, I'm mapping to miRBase hairpins.

    Any suggestions (Cufflinks or otherwise) about getting this kind of output would be greatly appreciated.

    Thanks!
    Vivek
  • hsmart
    Member
    • Dec 2009
    • 15

    #2
    Dear All,

    I am trying to use cufflinks to analyze RNA-seq data from two cell-lines. I used following commands:
    cuffcompare -i ~/Cufflink_files.txt -r ~/Homo_sapiens.GRCh37.60.gtf -R -p cell1_cell2 -o ~/cell1_cell2_results.txt
    cuffdiff -L cell1,cell2 -p 4 -N --FDR 0.05 -r ~/hg19.fa ~/cell1_cell2_results.combined.gtf ~/cell1_accepted_hits.bam ~/cell2_accepted_hits.bam -o ~/Cuffdiff/
    I have few questions regarding output of cufflinks:
    (1) None of the .diff output files (gene, cds, isoform, promoters, splicing etc) have gene name or gene id associated with it. How can I generate output with gene names? Do I need to change any parameter in cuffcompare?
    (2) Also, the locus region of the gene_exp.diff seems to be quite large (for example about 32 kb and includes cluster of 3 genes). So, how does cufflinks define a gene and boundaries related to it?
    (3) Also, the locus region of the isoform_exp.diff seems to be quite large (for example about 10 kb and includes entire gene). So, how does cufflinks define an isoform and boundaries related to it?
    (4) What type of statistical method does cufflinks use to calculate uncorrected p-value?
    (5) What is the meaning of column 7 and 8 (Reserved with value of 0) in splicing.diff file?
    (6) How do you compare FPKM and RPKM in terms of absolute values to consider if the gene is expressed above the background?

    I really appreciate your personal help regard these issues.

    Thanks,

    Rakesh

    Comment

    • honey
      Senior Member
      • Feb 2010
      • 151

      #3
      GTF file

      Rakesh,

      One of the first thing you may like to do is to use correct reference annotation GTF file as mentioned in this post
      Discussion of next-gen sequencing related bioinformatics: resources, algorithms, open source efforts, etc

      This will add gene names etc.

      and will solve some of your issues. So far as 0 in col 7 and 8 is concerned it is because of formatting of the output and are just reserved columns.

      Best

      Comment

      • hsmart
        Member
        • Dec 2009
        • 15

        #4
        Hi,

        Thank you so much for your help.
        It worked perfectly with
        awk '{print "chr"$0}' Homo_sapiens.GRCh37.60.gtf | sed 's/chrMT/chrM/g' > hg19.ensembl-for-tophat.gtf

        I really appriciate your help,

        Best wishes,

        Rakesh

        Comment

        Latest Articles

        Collapse

        • SEQadmin2
          Multiomic Liquid Biopsy: What DNA/RNA Panels Reveal That DNA Alone Can’t
          by SEQadmin2



          Tumors contain complex mixtures of cell populations that evolve in response to treatment and host-specific factors. Tissue biopsies provide only static snapshots of a tumor’s state. But what if we could follow that evolution over time using a minimally invasive technique?

          Liquid biopsies can detect tumor-derived material circulating in the bloodstream, providing a way to study treatment response, detect emerging resistance, and discover new biomarkers. Circulating
          ...
          Today, 09:55 AM
        • SEQadmin2
          New Genomics Technologies Take Aim at Long-Standing Limits
          by SEQadmin2


          Researchers using sequencing and genomics tools often have to make trade-offs. They can choose between speed or scale, short reads or long-range information, or targeted panels or a view of the whole transcriptome. New technologies that have been released this year are built to address those tough choices.

          We asked six companies the same four questions to learn about their latest products. The new technologies bring a lot to the table, including rethinking sequencing
          ...
          09-28-2026, 10:25 AM

        ad_right_rmr

        Collapse

        News

        Collapse

        Topics Statistics Last Post
        Started by SEQadmin2, Today, 05:39 AM
        0 responses
        9 views
        0 reactions
        Last Post SEQadmin2  
        Started by SEQadmin2, Yesterday, 09:56 AM
        0 responses
        11 views
        0 reactions
        Last Post SEQadmin2  
        Started by SEQadmin2, 10-09-2026, 11:14 AM
        0 responses
        25 views
        0 reactions
        Last Post SEQadmin2  
        Started by SEQadmin2, 09-29-2026, 09:51 AM
        0 responses
        76 views
        0 reactions
        Last Post SEQadmin2  
        Working...