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The ChIP-seq pipeline “Cistrome” integrated into UGENE allows one to do the following analysis steps: peak calling and annotating, motif search and gene ontology. ChIP-seq analysis is started from MACS tool. CEAS then takes peak regions and signal wiggle file to check which chromosome is is enriched with binding/modification sites, whether bindings events are significant at gene features like promoters, gene bodies, exons, introns or UTRs, and the signal aggregation at gene transcription start/end sites or meta-gene bodies (average all genes). Then peaks are investigated in these ways: 1.

1. to check which genes are nearby so can be regarded as potential regulated genes, then perform GO analysis;

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2. to check the conservation scores at the binding sites;

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2. the DNA motifs at binding sites.

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Note that it is originally based on the General ChIP-seq pipeline from the public Cistrome installation on the Galaxy workflow platform.

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To run a pipeline, use UGENE Workflow Designer. To open it select Tools -> Workflow Designer in the UGENE main menu. To read more about the Workflow Designer see UGENE documentation page. To run the pipeline you may use example data from the Sample Data Package that goes with this tutorial.

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Environment requirements: Before proceeding, please make sure that your computer is configured as follows:  The following software packages are installed: Python 2.7  R software environment  NumPy 1.7 (or greater)  Django 1.1.1 (or greater)  Make sure R and Python are added to the PATH environment variable. Move directory “cistrome” from the Cistrome Configuration Package, that goes with this tutorial, to the “data” subdirectory of the UGENE installation directory. Install required Bioconductor packages. To do it, please make sure your computer is connected to the internet, unpack “installRpackages.R” script from the Cistrome Configuration Package and run it as follows: On Linux/Mac OS X open a terminal and run commands: “sudo Rscript –vanilla installRpackages.R” It may be required to also run the following command on Linux: “sudo apt-get install libxml2-dev” On Windows search for “cmd” executable file, select “Run as administrator” item in its context menu and run command: “Rscript –vanilla installRpackages.R” Note that it takes some time to install the packages.

 

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The following scheme will appear: 

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