The new ChIP-seq and ATAC-seq functionality secures full workflows and analysis options. Below are some examples of typical use cases. 

ChIP-seq analysis typically involves the detection of ‘peaks’ in read coverage for regions where the protein binding sites are located.  The program supports peak detection using MACS2. The resulting peak files can then be merged into a consensus bed file which is used to generate a count matrix for the peaks. This enables the user to extend peak analysis beyond standard types and to evaluate custom regions of interest, such as promoters, structural hotspots, pseudogenes, personalized/non-reference genomes, etc. 

A count matrix can also be generated using a gtf-file for a truly gene-centered ChIP-seq analysis. If the experiment also includes RNA-seq data, it is possible to generate a RNA-seq count matrix and swap between the RNA-seq and ChIP-seq count matrixes during the analysis. The genome browser allows the user to annotate peaks and export the result as a bed file and the full power of the program is available, including many statistical tests, clustering and powerful visualization.

Once the most interesting peaks have been found using statistics or visual analysis, they may be included in follow up analysis as ‘active variables’; effectively filtering out all other variables for a more targeted approach. These active variables can then be used as a filter in the genome browser so that a detailed analysis of the peaks themselves can be performed, confirmed, and rendered into publication-quality figures.  

All the above functionality is also available for ATAC-seq data.
An upcoming webinar will explain how to work with ChIP-seq and ATAC-seq data, including peak detection and quantification of peaks. A data matrix of peak data is generated and can be used for visualization and statistical analyses of the standard plots.
 

UPCOMING WEBINAR: 
“The new Genome Browser with support for ChIP-seq and ATAC-seq data”
Date: June 29th, 2021
Time: 16:00 GMT (+1)     

Register HERE for webinar.

Learn more about the new version and watch short ChIP-seq video.