build_gene_activity_matrix {cicero} | R Documentation

## Calculate initial Cicero gene activity matrix

### Description

This function calculates the initial Cicero gene activity matrix. After this function, the activity matrix should be normalized with any comparison matrices using the function `normalize_gene_activities`.

### Usage

    build_gene_activity_matrix(input_cds, cicero_cons_info,
      site_weights = NULL, dist_thresh = 250000, coaccess_cutoff = 0.25)

### Arguments

`input_cds` | Binary sci-ATAC-seq input CDS. The input CDS must have a column in the fData table called "gene" which is the gene name if the site is a promoter, and `NA` if the site is distal.
`cicero_cons_info` | Cicero connections table, generally the output of `run_cicero`. This table is a data frame with three required columns named "Peak1", "Peak2", and "coaccess". Peak1 and Peak2 contain coordinates for the two compared elements, and coaccess contains their Cicero co-accessibility score.
`site_weights` | NULL or an individual weight for each site in input_cds.
`dist_thresh` | The maximum distance in base pairs between pairs of sites to include in the gene activity calculation.
`coaccess_cutoff` | The minimum Cicero co-accessibility score that should be considered connected.

### Value

Unnormalized gene activity matrix.

### 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 <- detectGenes(input_cds)
      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)
      cons <- run_cicero(cicero_cds, sample_genome, sample_num=2)

      data(gene_annotation_sample)
      gene_annotation_sub <- gene_annotation_sample[,c(1:3, 8)]
      names(gene_annotation_sub)[4] <- "gene"
      input_cds <- annotate_cds_by_site(input_cds, gene_annotation_sub)
      num_genes <- pData(input_cds)$num_genes_expressed
      names(num_genes) <- row.names(pData(input_cds))
      unnorm_ga <- build_gene_activity_matrix(input_cds, cons)

[Package cicero version 1.2.0 Index]