If the gene set falls at either the top (over-expressed) or bottom (under-expressed), it is thought to be related to the phenotypic differences. Researchers analyze whether the majority of genes in the set fall in the extremes of this list: the top and bottom of the list correspond to the largest differences in expression between the two cell types. In GSEA, DNA microarrays, or now RNA-Seq, are still performed and compared between two cell categories, but instead of focusing on individual genes in a long list, the focus is put on a gene set. A database of these predefined sets can be found at the Molecular signatures database (MSigDB). Gene set enrichment analysis uses a priori gene sets that have been grouped together by their involvement in the same biological pathway, or by proximal location on a chromosome. By doing so, this method resolves the problem of the undetectable, small changes in the expression of single genes. Gene Set Enrichment Analysis was developed to focus on the changes of expression in groups of a priori defined gene sets. Multiple genes are linked to a single biological pathway, and so it is the additive change in expression within gene sets that leads to the difference in phenotypic expression. However, this method of comparison is not sensitive enough to detect the subtle differences between the expression of individual genes, because diseases typically involve entire groups of genes. Microarrays on thousands of different genes were carried out, and comparisons the results of two different cell categories, e.g. In order to seek out genes associated with diseases, DNA microarrays were used to measure the amount of gene expression in different cells.
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