ATAC/DHS coverage of FCC libraries
Questions:
- What percentage of data falls within open chromatin regions?
- How many open chromatin regions are covered in each FCC assay?
Correlations of effect sizes among FCC assays
Questions:
- What are the correlations of effect sizes across different FCC assays?
Distributions of effect sizes across chromatin states
Questions:
- How do effect sizes differ across various chromatin states (e.g., promoters and enhancers)?
- Are certain chromatin states associated with higher or lower effect sizes in each assay?
Methods:
- Group regions by chromatin states (e.g., cCREs, ChromHMM).
- Compare effect sizes among different groups (e.g., promoters vs. enhancers).
Distributions of effect sizes across regions with different physical connectivity
Questions:
- How do effect sizes vary across regions with different physical connectivity?
- Is there a significant difference in effect sizes between regions with high loop counts and those with low loop counts?
- Are certain types of chromatin interactions (e.g., long-range vs. short-range loops) associated with distinct effect size distributions?
Methods:
- Group regions by loop counts or loop distance
- Compare effect sizes among different groups
Explain the variations of each FCC effect size by ChIP-seq annotations
Questions:
- How much variation in regulatory effects can be explained by ChIP-seq annotations?
- What is the predictivity of regulatory effects using ChIP-seq information?
Method:
- Regression: FCC ~ ChIP-seq
[????] Clustering the regions based on FCC data and ChIP-seq annotations
Questions:
- (Keith) are there features associated with active enhancers that differentiate them into different categories or subclasses
Method:
- Integrate the FCC data and ChIP-seq into a matrix (Option 1: z score; Option 2: peak calls)
- Clustering the matrix
- Visualize the matrix and cluster by UMAP dimentional reduction