PATHMiR
Getting started
The access address to PathMir is http://pathmir.imib.es, it is not necessary to introduce user and password, PathMir is free for all the scientific community. The main access page is Functional Analysis MiRNA.
Through this page we can introduce the miRNA, each one in a row, to find out the genes which regulate those miRNA. We must to select the miRNA specie that we are looking for.
Finally, it is necessary to indicate the level of evidence, Strong: Supported by strong experimental evidences (Reporter assay or Western blot), Weak: Supported by weak experimental evidences (Microarray or pSILAC). The P-value threshold is established at 0,05 by default.
There is the possibility of running two examples of miRNA with Homo Sapiens and Mus Musculus.
Once the parameters have been selected, we execute the ‘Run Enrichment Analysis’ which will return the results in various analyses, Pathways Enrichment, Gene Ontology Enrichment and Human Phenotype Ontology.
Pathways Enrichment
As an example we will see the results of Pathways Enrichment, through this option we can see the data table with the pathway name, the number of genes in the phenotype, the number of genes that regulate the introduced miRNA, and the P-value. There is also the possibility of sorting the table according to the number of genes in ascending or descending order and also by P-value.
It is important to note that all the data and graphs are downloadable and exportable in standard formats like csv, xls, pdf, png, svg etc.
If we want to list the genes involved in that set of miRNAs we must select the icon to the right of the table called ‘Gene features’, this will show us a list of the genes that are regulated by these.
In addition to having a table with the pathways, we can see two grahps, Whell plot and Bar plot, to see the interaction between the most statistically significant metabolic pathways and for each miRNA the number of genes that it regulates respectively.
Wheel Plot
To be able to see more easily the interaction between pathways, we must position over the pathway and the graph will illuminate those genes in common that are most statistically significant, depending on the line-thickness it will mean more number of genes between.
Bar plot
From this graph we can see for each path the number of DE Genes regulated and if we position on the bar we can see the Pathway name.
If we click on the bar we can see in a dialog the list of Genes and a link to Kegg where it will mark in red those genes involved.
We have performed the same analysis, for the remaining three components, with the Gene Ontology and the Human Phenotype.
Finding MiRNAs from phenotypes
By using this other option we can search for miRNA through one or several phenotypes. To do so, we must filter and select those phenotypes on which we want to make the search.
We select the type of evidence in the experiment, strong or weak, and finally we run ‘Estimate miRNA’, which will return a table with the information for each selected type miRNA, the mirtarBase identifier, the genes it regulates, the number of phenotypes involved and the papers that refer to this miRNA.
