Methods for Comparison of ChIP-Seq experiments
Since the ChIP-Seq technique was first developed in 2007, a lot of work has gone into developing methods for analyzing this data. Dozens of papers and several reviews have been published describing methods and tools for the analysis of individual ChIP-Seq experiments (references), but there has been far less effort devoted to methods for comparing the results from multiple ChIP-Seq location analysis experiments. A comparison between multiple ChIP-Seq experiments might be necessary for examining the occupancy of a single factor in multiple conditions or for comparing the occupancy of different factors in the same cell.
Two of the methods that are commonly used to compared the results of multiple ChIP-Sqee experiments are Venn Diagrams and clsutergrams (Figure ?). Venn diagrams show the number of enriched regions or genes that overlap between a set of ChIP-Seq datasets. One weakness of Venn diagram analysis is that it requires determining a threshold for enrichment in each dataset a priori, which is often problematic. Additionally, the Venn diagram analysis frequently underrepresentats the similarity between two different experiments. Two experiments that appear to be very similar might only be 50% overlapping in a Venn diagram analysis, and it is rare to observe two datasets overlapping more than 80%. Lsutergrams show this and that etv. The primary weakness of clsutergrams is tthey tend to highlight simialrities between datasets.
Magnitude of enrichement more important than hypergeometricc significance
Framptongram - cytoscape
Methods for es v sips compairosn
Normalization and Comparitive Analysis
No threshold, preserve order
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