Data Mining

The results of statistical analysis yield lists of statistically significant genes or SNPs. This information does not directly give biological insights into the system under study,especially when the lists are long. Additional analyses can often help to transform these lists of genes into information that is much closer to  biological systems.

Gene list enrichment

P53 Signaling Pathway

Individual genes can be related to certain biologically relevant terms (GO - gene ontology). Randomly selected genes do not  show any enrichment in any particular term and  reflect the different term proportions of the original data set, the genes of the microarray, for instance. It is possible to test if the list shows an enrichment in any term. If statistically relevant, this enrichment is then related to the biological conditions under study. The results can be compared to any type of list for enrichment, especially to carefully selected lists of genes or terms of particular interest for the  system under investigation.

Pathway analysis

Another rich source of biologically relevant information are   gene pathways (see, for instance, the Kyoto Encyclopedia of Genes and Genomes - KEGG pathways). Using similar statistical techniques to those described above, that is, comparing the perturbation effect of the statistically differentially expressed genes on  pathways, it is possible to link a given pathway with the list of genes, and thus with the biological hypothesis under investigation..

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