Thank you for choosing to use PEACE. PEACE is an acronym for Parallel Environment for Assembly and Clustering of gene Expressions. As the name suggests, the primary objective of PEACE is to ease clustering and analysis of Expressed Sequence Tags (ESTs). EST clustering is a computationally demanding task and clustering large EST data sets requires hours of compute (or CPU) time. In order to reduce wall clock time, PEACE has the ability to cluster ESTs in parallel using a modern supercomputing cluster. You can read more about PEACE and associated tools via the PEACE website http://www.peace-tools.org/.

Here is a quick overview of the various steps that are needed to perform some basic EST clustering and analysis:

Step 1: Server/Supercomputing cluster setup
The first step in the process is to create a server entry in PEACE GUI. Click on the Add Server tool in the main toolbar to launch the wizard to add a server. This wizard guides you through the process of installing the core PEACE clustering engine on a Linux/Unix machine or supercomputing cluster. You need to have a valid login to the machine on which PEACE clustering engine will run.

Step 2: Create Data Set
Once you have successfully added a server entry, the next step is to create a Data Set. A data set contains the EST (FASTA) file and associated clustering data files. Click on the New Data Set tool in the main toolbar to launch the wizard to create a new data set from an existing EST (FASTA) file.

Step 3: Start Job to perform clustering
Next step is to launch a job to analyze a selected EST (FASTA) file and identify clusters. This task is performed by the New Job/MST wizard. This wizard can be launched via the New Job/MST tool. The default values in this wizard are preset and provide a good start on clustering with PEACE.

Step 4: View/Analyze Clusters
Once the clustering job is complete, the generated data files are copied by PEACE from the server to your local machine. The files will appear under the data set in the Hierarchy tab. Right click on the appropriate entry and select the appropriate view to view the clustered ESTs.