Unconfigured Ad

Collapse
X
 
  • Filter
  • Time
  • Show
Clear All
new posts
  • MayurDivate
    Junior Member
    • Feb 2014
    • 2

    Significant Biology analysis using differentially expressed genes

    Hello everyone,

    Best wishes.

    I want find out statistically significant pathway and gene ontology of miRNAs annotation of deep sequencing data.

    I have annotated known and Novel miRNAs. Based on annotation, Is there any method to find significant pathways and GOs ?

    One I know is GoElite by gladstone institute.
    link: http://www.genmapp.org/go_elite/help_main.htm

    but with this i am not getting any significant GOs and Pathways.


    If you have done significant biology analysis or heard about any tool please let me know.

    Thanks
  • dpryan
    Devon Ryan
    • Jul 2011
    • 3478

    #2
    You'll need to see what the miRNAs are targeting (give targetscan a try) and then use their GO terms.

    Comment

    • MayurDivate
      Junior Member
      • Feb 2014
      • 2

      #3
      @dpryan

      I have annotation for miRNAs on the basis of their targets. I want to out of all GOs and Pathways that I got in annotation which are statistically significant ?

      By means of Z-score , p-value etc.

      Comment

      • dpryan
        Devon Ryan
        • Jul 2011
        • 3478

        #4
        If you already have the GO and pathway associations, then just go ahead with the hypergeometric test.

        Comment

        • chirag.parsania
          Junior Member
          • Nov 2013
          • 2

          #5
          Hi Mayur,

          Instead of GOelite you can try many other tools. There would be chances that you haven't crated proper background database in DESeq and so you are not getting significant p-val. P-val depends on what background data you are suppling. I would suggest download the cytoscap and add a plugin named "Bingo". In this plug in you just need to supply you query gene list and go database file. go database file you can get from GO website for your organism http://geneontology.org/page/download-annotations

          You will get all the detail of background frequency , p val and network as well.

          Hope this would help

          Comment

          • AndrewO
            Member
            • Feb 2014
            • 15

            #6
            If you have gene-expression data, you can use iPathwayGuide to get statistically significant GO terms, Pathways, predicted miRNAs (based on gene-expression of the target genes), and enriched diseases.

            You can see more in this post, or go directly to the website here.

            Click the image below to view a short 3:00 min overview video:

            Comment

            Latest Articles

            Collapse

            • SEQadmin2
              Advanced Sequencing Platforms Tackle Neuroscience’s Toughest Genomics Problems
              by SEQadmin2



              Genomics studies in neuroscience face a special challenge due to the brain’s complexity and scarcity of samples. Mapping changes in cell type and state using conventional next-generation sequencing methods remains challenging. Advances in technologies like single-cell sequencing, spatial transcriptomics, and long-read sequencing have opened the door to deeper studies of the brain and diseases like Alzheimer’s, amyotrophic lateral sclerosis (ALS), and schizophrenia.
              ...
              07-09-2026, 11:10 AM
            • SEQadmin2
              Cancer Drug Resistance: The Lingering Barrier to Rising Survival
              by SEQadmin2



              Cancer survival rates have significantly increased in the last few decades in the United States, reaching a combined 70% 5-year survival rate by 2021. Behind this number, there are years of research to find new therapies, drug targets, and early detection methods. But there is one core challenge that keeps slowing down these advances, and it’s about drug resistance.

              There is no single reason why many patients don’t respond to treatment as expected. Cancer is...
              07-08-2026, 05:17 AM
            • GATTACAT
              Reply to Nine Things a Sample Prep Scientist Thinks About Before Sequencing
              by GATTACAT
              Love this - good data definitely starts from good input, and poor input can only give relatively poor data. I particularly like the mention of Nanodrop/absorbance based methods for quantification. It's such a toss up if you'll get an accurate reading or what amounts to a randomly generated number, and a lot of library/sequencing related issues can be traced back to poor quant.
              07-01-2026, 11:43 AM

            ad_right_rmr

            Collapse

            News

            Collapse

            Topics Statistics Last Post
            Started by SEQadmin2, 07-13-2026, 10:26 AM
            0 responses
            20 views
            0 reactions
            Last Post SEQadmin2  
            Started by SEQadmin2, 07-09-2026, 10:04 AM
            0 responses
            30 views
            0 reactions
            Last Post SEQadmin2  
            Started by SEQadmin2, 07-08-2026, 10:08 AM
            0 responses
            20 views
            0 reactions
            Last Post SEQadmin2  
            Started by SEQadmin2, 07-07-2026, 11:05 AM
            0 responses
            34 views
            0 reactions
            Last Post SEQadmin2  
            Working...