generate_cicero_models {cicero} | R Documentation

## Generate cicero models

### Description

Function to generate graphical lasso models on all sites in a CDS object within overlapping genomic windows.

### Usage

    generate_cicero_models(
      cds,
      distance_parameter,
      s = 0.75,
      window = 5e+05,
      max_elements = 200,
      genomic_coords = cicero::human.hg19.genome
    )

### Arguments

`cds` | A cicero CDS object generated using `make_cicero_cds`.
`distance_parameter` | Distance based penalty parameter value. Generally, the mean of the calculated `distance_parameter` values from `estimate_distance_parameter`.
`s` | Power law value. See details.
`window` | Size of the genomic window to query, in base pairs.
`max_elements` | Maximum number of elements per window allowed. Prevents very large models from slowing performance.
`genomic_coords` | Either a data frame or a path (character) to a file with chromosome lengths. The file should have two columns, the first is the chromosome name (ex. "chr1") and the second is the chromosome length in base pairs. See `data(human.hg19.genome)` for an example. If a file, should be tab-separated and without header.

### Details

The purpose of this function is to compute the raw covariances between each pair of sites within overlapping windows of the genome. Within each window, the function then estimates a regularized correlation matrix using the graphical LASSO (Friedman et al., 2008), penalizing pairs of distant sites more than proximal sites. The scaling parameter, `distance_parameter`, in combination with the power law value `s` determines the distance-based penalty.

The parameter `s` is a constant that captures the power-law distribution of contact frequencies between different locations in the genome as a function of their linear distance. For a complete discussion of the various polymer models of DNA packed into the nucleus and of justifiable values for s, we refer readers to (Dekker et al., 2013) for a discussion of justifiable values for s. We use a value of 0.75 by default in Cicero, which corresponds to the “tension globule” polymer model of DNA (Sanborn et al., 2015). This parameter must be the same as the s parameter for `estimate_distance_parameter`.

Further details are available in the publication that accompanies this package. Run `citation("cicero")` for publication details.

### Value

A list of results for each window. Either a `glasso` object, or a character description of why the window was skipped. This list can be directly input into `assemble_connections` to create a reconciled list of cicero co-accessibility scores.

### References

- Dekker, J., Marti-Renom, M.A., and Mirny, L.A. (2013). Exploring the three-dimensional organization of genomes: interpreting chromatin interaction data. Nat. Rev. Genet. 14, 390–403.

- Friedman, J., Hastie, T., and Tibshirani, R. (2008). Sparse inverse covariance estimation with the graphical lasso. Biostatistics 9, 432–441.

- Sanborn, A.L., Rao, S.S.P., Huang, S.-C., Durand, N.C., Huntley, M.H., Jewett, A.I., Bochkov, I.D., Chinnappan, D., Cutkosky, A., Li, J., et al. (2015). Chromatin extrusion explains key features of loop and domain formation in wild-type and engineered genomes. Proc. Natl. Acad. Sci. U. S. A. 112, E6456–E6465.

### See Also

`estimate_distance_parameter`

### Examples

      data("cicero_data")
      data("human.hg19.genome")
      sample_genome <- subset(human.hg19.genome, V1 == "chr18")
      sample_genome$V2[1] <- 100000
      input_cds <- make_atac_cds(cicero_data, binarize = TRUE)
      input_cds <- reduceDimension(input_cds, max_components = 2, num_dim=6,
                                   reduction_method = 'tSNE',
                                   norm_method = "none")
      tsne_coords <- t(reducedDimA(input_cds))
      row.names(tsne_coords) <- row.names(pData(input_cds))
      cicero_cds <- make_cicero_cds(input_cds, reduced_coordinates = tsne_coords)
      model_output <- generate_cicero_models(cicero_cds,
                                             distance_parameter = 0.3,
                                             genomic_coords = sample_genome)

[Package cicero version 1.4.4 Index]