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GO Enrichment Analysis Service

One of the main applications of the GO is to perform enrichment analysis on gene or protein sets. For instance, given a set of proteins that are up-regulated under certain conditions, an enrichment analysis will find which GO terms are over-represented (or under-represented) via annotations for that protein set. The GO enrichment analysis have proven to be remarkably useful for the exploring of functional and biological significance from very large datasets, such as Mass Spectral data and microarray results. The GO enrichment analysis also facilitates the organization of data from novel, (or fully annotated) genomes and the comparison of biological functions between clade members and across clades. Now, Scientists at Creative Proteomics are proud to tell you we are open to help you with GO Enrichment Analysis Service!

Creative Proteomics can provide GO Enrichment Analysis Service with several optional statistical methods:

  • Hypergeometric test/Fisher's exact test
  • Bayesian model
  • Z-statistic
  • Network analysis
  • More choices if you need!

GO Enrichment Analysis Service at Creative Proteomics includes the following steps:

  • Determine the annotated GO terms and all splits
  • Count the number of appearances of each GO term for the proteins in the tested set as well as in the reference set
  • Calculate a p-value representing the probability that the enriched numbers of counts could have resulted from randomly distributing this GO term between the tested set and the reference set

The enrichment results describes the significant shared GO terms (or parents of GO terms) used to describe the set of proteins of interest, the background frequency, the sample frequency, and p-value, an indication of over (or under) representation for each term. P-value is the probability or chance of seeing at least x number of proteins out of the total n proteins in the list annotated to a particular GO term, given the proportion of proteins in the identified proteins that are annotated to that GO Term. That is, the GO terms shared by the proteins in the user's list are compared to the distribution of background annotation. The closer the p-value is to zero, the more significant the specific GO term associated with the group of proteins is (i.e. the less likely the observed annotation of the specific GO term to a set of genes occurs by chance).

GO Enrichment Analysis Service

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As one of the leading omics industry company in the word! Creative Proteomics Now is opening to provide the first class service for our customers. With years’ rich experience in bioinformatics, Creative Proteomics can provide our customer with high quality GO enrichment analysis service! Please contact us without hesitating for more detailed information!


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