No announcement yet.

Significant Biology analysis using differentially expressed genes

  • Filter
  • Time
  • Show
Clear All
new posts

  • 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.

    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.


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


    • #3

      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.


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


        • #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

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

          Hope this would help


          • #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: