CD ComputaBio provides cutting-edge software-based virtual services to empower researchers, but we do not offer free software packages.
Gene Ontology (GO) is an international standard classification system for gene function. GO enrichment analysis is to classify the differential genes according to GO, and perform the significance analysis based on the discrete distribution of the classification results, the error rate analysis, and the enrichment analysis to obtain the gene function classification that is significantly related to the experimental purpose. This classification is the most important functional difference that leads to differences in sample traits. In the data analysis of the chip, the researcher can find out which changed genes belong to a common GO functional branch, and use statistical methods to check whether the results are statistically significant, so as to obtain which biological functions the changed genes are mainly involved in.
Overall solutions
🧬 RNA-seq Functional Interpretation
Translate differential gene expression into biological meaning
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.
Our services
Project name
GO enrichment service
Our service process
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.
Screening cycle
Decide according to your needs.
Deliverables
We provide you with raw data and analysis service.
Why work with us instead of free quantum chemistry tools?
Feature
Our Service
Standard Online Tools
Data preprocessing & QC
✓
Limited
Customized background selection
✓
Default only
Advanced statistical analysis
✓
Basic
Expert biological interpretation
✓
✗
Multi-omics integration
✓
✗
Functional clustering & redundancy reduction
✓
Limited
Visualization quality
Publication-ready
Basic plots
Hypothesis generation support
✓
✗
Project-specific analysis strategy
✓
Fixed
Clear technical reporting
✓
Minimal
Collaboration process
We follow a structured, transparent, and highly collaborative workflow to ensure your research objectives are fully understood and translated into meaningful biological insights.
1
Project Consultation & Objective Alignment
We start by understanding your research goals, dataset type, and specific biological questions.
Our team performs thorough data quality assessment and preparation.
✔ Data format check and normalization
✔ Filtering low-quality or low-expression genes
✔ Background gene set definition
3
GO Enrichment Analysis Execution
We apply optimized statistical methods tailored to your dataset.
✔ Accurate enrichment analysis
✔ Multiple testing correction
✔ Custom parameter optimization
4
Functional Interpretation & Insight Extraction
We translate enrichment results into clear biological meaning.
✔ Identify key biological processes and pathways
✔ Highlight critical genes and regulatory mechanisms
✔ Connect findings to your research context
5
Visualization & Reporting
We deliver clear, publication-ready outputs.
✔ Dot plots, bar charts, enrichment maps
✔ Functional clustering visualization
✔ Structured and easy-to-understand report
✔ Answer your scientific questions
What you'll receive
Deliverable
Description
Enriched GO Terms Table
Statistically significant GO categories
Functional Classification
Biological process / molecular function breakdown
Visualization Figures
Dot plots, bar charts, enrichment maps
Pathway & Functional Insights
Interpretation of biological meaning
Candidate Gene List
Key genes driving enrichment
Custom Analysis Report
Actionable conclusions & recommendations
Publication-Ready Outputs
Figures & formatted tables
Published data
Case 1: NeVOmics: Network-based Visualization for Omics
The NeVOmics framework addresses the "long-list challenge" in omics research, where scientists often struggle to interpret thousands of genes or proteins. To streamline functional analysis, the authors developed NeVOmics, which utilizes hypergeometric distribution tests to calculate statistical significance while integrating with Gene Ontology (GO) and KEGG databases. This integration allows for the construction of sophisticated functional networks that go beyond simple lists.
Fig 1. Schematic overview of the steps performed by NeVOmics.1
Frequently Asked Questions
CD ComputaBio' GO enrichment analysis can significantly reduce the cost and labor of the subsequent experiments. GO enrichment analysis is a personalized and customized innovative scientific research service. Each project needs to be evaluated before the corresponding analysis plan and price can be determined. If you want to know more about service prices or technical details, please feel free to contact us.
Reference:
Zúñiga-León E, Carrasco-Navarro U, Fierro F. NeVOmics: an enrichment tool for gene ontology and functional network analysis and visualization of data from OMICs technologies[J]. Genes, 2018, 9(12): 569.
Fig 1. Schematic overview of the steps performed by NeVOmics.1