Application Build: 246     Database Build: 2008-04

Getting Started

Choosing the Appropriate GoMiner Version

GoMiner and High-Throughput GoMiner have similar processing capabilities, but which version is best for your analysis depends on your situation. The following guidelines will help you chose:

The original GoMiner interface, which we sometimes call Classic or GUI GoMiner, is well-suited if you:

• Have a few small data sets
• Are interested in examining the ontology graphically and interactively
• Are interested in links to external resources that provide detailed information for genes and GO categories
• Want precise control over when to upgrade your application and database

GoMiner can also be used to handle large data sets; To experience a reasonable response time with large data sets, we strongly recommend that you set up a local copy of the GO database.

The web interface of High-Throughput GoMiner, is well suited if you:

• Have either small or large data sets
• Have either a single or multiple changed gene lists for the same total gene list (e.g. a time course study)
• Are interested in generating Clustered Image Maps of your results
• Are interested in the relationship of transcription factor binding sites and GO categories

High-Throughput GoMiner is particularly useful if you want to process large data sets, but do not want to set up your own local database. High-Throughput GoMiner automates many of the repetitive processing that you would need to do manually in GUI GoMiner, such as saving the various export files.

GoMiner and Hight-Throughput GoMiner both have command-line interfaces as well. These can be useful if you would like to automate processing using scripts. In either case, we would recommend that you set up a local copy of the GO database if you plan to do extensive automated processing.

GoMiner System Requirements

If you have not already done so, check the system requirements, and install GoMiner™

GoMiner Examples

We have provided a Quick Start to guide you through some examples using GoMiner. The following sample input files are referenced in the guide, and can be used on their own to explore the tool.

• List of all genes in experiment
• List of changed genes (1 column)
• List of changed genes (2 column)

We have also provided an example that makes use of GoMiner's synonym lookup feature. This is a yeast data set that is annotated using the ORF notation.

• List of all genes in experiment
• List of changed genes (1 column)

Examples formatted for use in the High-Throughput GoMiner are also available.

We would like to hear from you. You can reach the team via email.

GoMiner was originally developed jointly by the Genomics and Bioinformatics Group (GBG) of LMP, NCI, NIH and the Medical Informatics and Bioimaging group of BME, Georgia Tech/Emory University. It is now maintained and under continuing development by GBG.

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