Gene ontology (GO), enrichment analysis has been incorporated into the gene expression, microRNA expression, exon, copy number, tiling, ChIP-Seq, RNA-Seq, miRNA-Seq and methylation workflows. The Gene Ontology Consortium website provides an excellent overview for new and experienced users of GO analysis. In brief, the common nomenclature of genes and gene products has been used to group genes into a functional hierarchy. This enables analyses to be compared across all types of genomic data, even data from different species. A broader understanding of experimental results is possible by grouping genes of interest into biological processes, cellular components and molecular functions of the genes. With the GO enrichment tool in Partek® Genomics Suite® you can take a list of genes (e.g. significantly differentially expressed genes) and see how they group in the functional hierarchy. This is analogous to going from looking at individual trees (genes) to see how the whole forest is organized.

This tutorial illustrates how to:

Note: the workflow described below is enabled in Partek Genomics Suite version 7.0 software. Please fill out the form at www.partek.com/PartekSupport to request this version or use the Help > Check for Updates command to check whether you have the latest released version. The screenshots shown within this tutorial may vary across platforms and across different versions of Partek Genomics Suite.

Description of the Data Set

This tutorial will provide a step-by-step guide to performing GO enrichment analysis. The data set used is based on 51 subjects ran on the Illumina Human Fre-8 BeadChip platform. Twenty-six of the subjects were categorized as "Young" with an age range of 18 to 28. The other 25 subjects were categorized as "Old" with an age range of 65 to 84. Skeletal muscle, a type of striated muscle tissue, was obtained via biopsy from each subject. The skeletal muscle cells had the total RNA extracted, prepared and run on the BeadChips producing the data that is used for this tutorial.

The paper this data is based on can be found at PLOS.

Data and associated files for this tutorial can be downloaded by going to Help > On-line Tutorials on the main menu toolbar within the Partek Genomics Suite software or by using this link - GO Enrichment.

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