In several omic scenarios we have a group of genes of interest from a transcriptomic analysis, or from different genomic studies where we have found causal variants of a certain disease or even a selection of genes obtained after a literature review.

We would like to know what functions are behind this group of genes. Through the following practical cases, we will know in detail what strategies and tools we can use in the functional characterization

1. Functional evaluation of the effect of hormone T3 in RNA-Seq study
2. Functional characterization in genes associated to retinal dystrophies
3. Functional profiling in transcriptomics differences between lung and kidney cancers
4. more PANTHER exercises

1. Functional evaluation of the effect of hormone T3 in RNA-Seq study (mdgsa package)
2. Functional profiling analysis (clusterProfiler package)

• Activity 1; Activity 2; Activity 3; Activity 4; More activities

After the detection of biomarkers of interest, we would like to know what functions are behind these genes or significant microRNAs. For that we can continue the analysis with various characterization tools especially oriented to small RNAs:

• omiRas: web server for the annotation, comparison and visualization of non-coding RNAs.
• miRNet: an integrated platform linking miRNAs, targets & functions.
• mirPath v.3: a miRNA pathway analysis web-server.

1. Functional profiling in microRNAs study about lung cancer