Seqanswers Leaderboard Ad

Collapse

Announcement

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

  • 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

  • #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


    • #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


      • #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

        • seqadmin
          Current Approaches to Protein Sequencing
          by seqadmin


          Proteins are often described as the workhorses of the cell, and identifying their sequences is key to understanding their role in biological processes and disease. Currently, the most common technique used to determine protein sequences is mass spectrometry. While still a valuable tool, mass spectrometry faces several limitations and requires a highly experienced scientist familiar with the equipment to operate it. Additionally, other proteomic methods, like affinity assays, are constrained...
          04-04-2024, 04:25 PM
        • seqadmin
          Strategies for Sequencing Challenging Samples
          by seqadmin


          Despite advancements in sequencing platforms and related sample preparation technologies, certain sample types continue to present significant challenges that can compromise sequencing results. Pedro Echave, Senior Manager of the Global Business Segment at Revvity, explained that the success of a sequencing experiment ultimately depends on the amount and integrity of the nucleic acid template (RNA or DNA) obtained from a sample. “The better the quality of the nucleic acid isolated...
          03-22-2024, 06:39 AM

        ad_right_rmr

        Collapse

        News

        Collapse

        Topics Statistics Last Post
        Started by seqadmin, 04-11-2024, 12:08 PM
        0 responses
        17 views
        0 likes
        Last Post seqadmin  
        Started by seqadmin, 04-10-2024, 10:19 PM
        0 responses
        22 views
        0 likes
        Last Post seqadmin  
        Started by seqadmin, 04-10-2024, 09:21 AM
        0 responses
        16 views
        0 likes
        Last Post seqadmin  
        Started by seqadmin, 04-04-2024, 09:00 AM
        0 responses
        46 views
        0 likes
        Last Post seqadmin  
        Working...
        X