Seqanswers Leaderboard Ad

Collapse

Announcement

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

  • Comparison of experimental groups in Cufflinks

    Hi all,

    I am analyzing Illumina-generated RNAseq data (63bp paired end reads). I have three experimental groups: X, Y, Z. I would like to find the similarities in alternative splicing between X and Z that are NOT present in Y. I am struggling with the best way to accomplish this with the output files from Cufflinks (and cuffdiff). Should I just compare FPKMs for each sample (from the tracking files) or is there a way I could take advantage of the stats run in cuffdiff? Which output file would be the helpful in this situation?

    I have successfully run all the parts of my pipeline...It's just that tricky bit of figuring out the best way to visualize/summarize/prioritize the data that's giving me trouble.

    I would greatly appreciate any advice, comments, etc. Thanks!

  • #2
    Originally posted by ega2d View Post
    Hi all,

    I am analyzing Illumina-generated RNAseq data (63bp paired end reads). I have three experimental groups: X, Y, Z. I would like to find the similarities in alternative splicing between X and Z that are NOT present in Y. I am struggling with the best way to accomplish this with the output files from Cufflinks (and cuffdiff). Should I just compare FPKMs for each sample (from the tracking files) or is there a way I could take advantage of the stats run in cuffdiff? Which output file would be the helpful in this situation?

    I have successfully run all the parts of my pipeline...It's just that tricky bit of figuring out the best way to visualize/summarize/prioritize the data that's giving me trouble.

    I would greatly appreciate any advice, comments, etc. Thanks!
    This really depends on what ou are looking for. Perhaps the easiest way is to take all of the genes that show up as significant for X, Y, and Z, and run them through a Venn Diagram like Venny.

    Comment

    Latest Articles

    Collapse

    • seqadmin
      Genetic Variation in Immunogenetics and Antibody Diversity
      by seqadmin



      The field of immunogenetics explores how genetic variations influence immune responses and susceptibility to disease. In a recent SEQanswers webinar, Oscar Rodriguez, Ph.D., Postdoctoral Researcher at the University of Louisville, and Ruben Martínez Barricarte, Ph.D., Assistant Professor of Medicine at Vanderbilt University, shared recent advancements in immunogenetics. This article discusses their research on genetic variation in antibody loci, antibody production processes,...
      11-06-2024, 07:24 PM
    • seqadmin
      Choosing Between NGS and qPCR
      by seqadmin



      Next-generation sequencing (NGS) and quantitative polymerase chain reaction (qPCR) are essential techniques for investigating the genome, transcriptome, and epigenome. In many cases, choosing the appropriate technique is straightforward, but in others, it can be more challenging to determine the most effective option. A simple distinction is that smaller, more focused projects are typically better suited for qPCR, while larger, more complex datasets benefit from NGS. However,...
      10-18-2024, 07:11 AM

    ad_right_rmr

    Collapse

    News

    Collapse

    Topics Statistics Last Post
    Started by seqadmin, 11-08-2024, 11:09 AM
    0 responses
    220 views
    0 likes
    Last Post seqadmin  
    Started by seqadmin, 11-08-2024, 06:13 AM
    0 responses
    161 views
    0 likes
    Last Post seqadmin  
    Started by seqadmin, 11-01-2024, 06:09 AM
    0 responses
    80 views
    0 likes
    Last Post seqadmin  
    Started by seqadmin, 10-30-2024, 05:31 AM
    0 responses
    27 views
    0 likes
    Last Post seqadmin  
    Working...
    X