generate_cicero_models: Generate cicero models

In cicero: Precict cis-co-accessibility from single-cell chromatin accessibility data

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)

cicero documentation built on Dec. 10, 2020, 2 a.m.