Post process cicero co-accessibility scores to extract modules of sites that are co-accessible.
Data frame of connections with columns: Peak1, Peak2,
coaccess. Generally, the output of
Numeric, co-accessibility score threshold to impose. Overrides automatic calculation.
The number of digits to calculate cutoff to. Default is 2 (0.01 tolerance)
CCANs are calculated by first specifying a minimum co-accessibility
score and then using the Louvain community detection algorithm on the
subgraph induced by excluding edges below this score. For this function,
either the user can specify the minimum co-accessibility using
coaccess_cutoff_override, or the cutoff can be calculated
automatically by optimizing for CCAN number. The cutoff calculation can be
slow, so users may wish to use the
initially calculating the cutoff to speed future runs.
Data frame with two columns - Peak and CCAN. CCAN column indicates CCAN assignment. Peaks not included in a CCAN are not returned.
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## Not run: data("cicero_data") set.seed(18) data("human.hg19.genome") sample_genome <- subset(human.hg19.genome, V1 == "chr18") sample_genome$V2 <- 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) cicero_cons <- run_cicero(cicero_cds, sample_genome, sample_num = 2) ccan_assigns <- generate_ccans(cicero_cons) ## End(Not run)
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