I have dataset containing thousands of miRNAs associated with a disease collected from miRTarBase. I need some idea, about what information I can deduce/predict with in-silico/bioinformatic analysis of those.
Thanks in advance.
You can do the following things:
Step1: Classify the downloaded data-set into two classes: up- and down-regulated miRNAs.
Step2: Search for possible targets (meta-analysis) on these two classes of miRNAs by using Target prediction databases e.g., miRWalk2.0.
Step3: Carry out pathway and GO enrichment analysis separately on the target genes obtained on the above classes.
Till these steps, you will have information on the biological cascades that may be involved in your disease of interest and could be regulated by up- and down-regulated miRNAs.
Next steps would be:
Step4. download m- and mi-RNA microarrays profiling data on your disease of interest from GEO database and perform data analysis to obtain significant genes/miRNAs (up- and/or down-regulated).
Step5. Repeat step2 for significant miRNAs and step3 for both target genes obtained on significant miRNAs as well as on the significant genes resulted from mRNA microarrays.
Step6. Overlap all the three data-sets and focus on the common findings.
Step7. Correlated your findings with literature.
You can further find out the possible role of SNPs related to miRNAs regulation in your disease of interest.
I hope this helps.
Best wishes,
Harsh
http://zmf.umm.uni-heidelberg.de/apps/zmf/mirwalk2/
Mostly the data in a databases are validated experimentally by any valid assays like Western Blot, Microarray and Next Generation Sequencing experiments. So you can find out following analysis based on that data...
1) MicroRNA Expression Profile
2) Target Gene Expression Profile
3) Relation between MicroRNA & Targeted Gene
4) Regulatory network of MicroRNA
5) Disease Target Information
6) MicroRNA & Target Interaction
7) Up and Down Regulated MicroRNAs
You can do the following things:
Step1: Classify the downloaded data-set into two classes: up- and down-regulated miRNAs.
Step2: Search for possible targets (meta-analysis) on these two classes of miRNAs by using Target prediction databases e.g., miRWalk2.0.
Step3: Carry out pathway and GO enrichment analysis separately on the target genes obtained on the above classes.
Till these steps, you will have information on the biological cascades that may be involved in your disease of interest and could be regulated by up- and down-regulated miRNAs.
Next steps would be:
Step4. download m- and mi-RNA microarrays profiling data on your disease of interest from GEO database and perform data analysis to obtain significant genes/miRNAs (up- and/or down-regulated).
Step5. Repeat step2 for significant miRNAs and step3 for both target genes obtained on significant miRNAs as well as on the significant genes resulted from mRNA microarrays.
Step6. Overlap all the three data-sets and focus on the common findings.
Step7. Correlated your findings with literature.
You can further find out the possible role of SNPs related to miRNAs regulation in your disease of interest.
I hope this helps.
Best wishes,
Harsh
http://zmf.umm.uni-heidelberg.de/apps/zmf/mirwalk2/
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