Seqanswers Leaderboard Ad

Collapse

Announcement

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

  • No significant genes in RNA-seq analyses

    Hi all
    I am doing RNA-seq analyses using tophat and cufflinks. I followed all the steps of nature protocol papers without any problem except the 'cummRbund' portion.

    I am adding selected snippet results below.

    Code:
    > 
    cuff_data <- readCufflinks("diff_out")
    > cuff_data
    CuffSet instance with:
    	 2 samples
    	 35210 genes
    	 65828 isoforms
    	 46226 TSS
    	 24611 CDS
    	 35210 promoters
    	 46226 splicing
    	 20203 relCDS
    > csVolcano(genes(cuff_data), 'C1', 'C2')
    Warning message:
    Removed 6924 rows containing missing values (geom_point). 
    > gene.diff[gene.diff$significant=='yes',]
     [1] gene_id          sample_1         sample_2         status           value_1          value_2          log2_fold_change test_stat       
     [9] p_value          q_value          significant     
    <0 rows> (or 0-length row.names)
    > getSig(cuff_data,alpha=0.05,level='genes')
    character(0)
    > mySigGeneIds<-getSig(cuff_data,alpha=0.5,level='genes')
    > getSig(cuff_data,alpha=0.5,level='genes')
    character(0)
    > length(getSig(cuff_data,alpha=0.9,level='genes'))
    [1] 6759
    I am amazed not to see anything differentially expressed. I am wondering if I did any mistake during the entire run.
    My 'volcanoplot' also does not show any significant point in the label, however, I see some points that are above 2.0 on y-axis, demonstrating a p-value of 0.001.

    I read some other posts suggesting to use edgeR.


    Thanks and help appreciated
    Last edited by fahim; 03-26-2013, 07:55 AM.

Latest Articles

Collapse

  • seqadmin
    Essential Discoveries and Tools in Epitranscriptomics
    by seqadmin




    The field of epigenetics has traditionally concentrated more on DNA and how changes like methylation and phosphorylation of histones impact gene expression and regulation. However, our increased understanding of RNA modifications and their importance in cellular processes has led to a rise in epitranscriptomics research. “Epitranscriptomics brings together the concepts of epigenetics and gene expression,” explained Adrien Leger, PhD, Principal Research Scientist...
    04-22-2024, 07:01 AM
  • 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

ad_right_rmr

Collapse

News

Collapse

Topics Statistics Last Post
Started by seqadmin, 04-25-2024, 11:49 AM
0 responses
19 views
0 likes
Last Post seqadmin  
Started by seqadmin, 04-24-2024, 08:47 AM
0 responses
18 views
0 likes
Last Post seqadmin  
Started by seqadmin, 04-11-2024, 12:08 PM
0 responses
62 views
0 likes
Last Post seqadmin  
Started by seqadmin, 04-10-2024, 10:19 PM
0 responses
60 views
0 likes
Last Post seqadmin  
Working...
X