Run all LR Downstream analysis

This function loads the single conditions LR outputs and return the LR network based analysis. It assumes that the table present the following columns ('source','target','gene_A','gene_B','type_gene_A','type_gene_B','MeanLR') measure

Usage

generate_report(
  lrpaths,
  genes = NULL,
  tf_genes = NULL,
  out_path,
  sep = ",",
  threshold = 0,
  colors = NULL,
  out_file = NULL,
  report = TRUE,
  output_fmt = "html_document",
  sel_columns = c("source", "target", "gene_A", "gene_B", "type_gene_A", "type_gene_B",
    "MeanLR"),
  org = "hsa",
  comparison = NULL
)

Arguments

lrpaths

Paths of single condition LR data

genes

list of genes to be considered in the sankey plots

out_path

output directory path

sep

character used on csv

threshold

percentage of edges to be pruned

colors

celltypes colorscheme

out_file

output file names

report

decide if a report is generated or not

output_fmt

rmarkdown render output format parameter

sel_columns

columns from data

Value

Rmarkdown report all objects from each step

Examples

paths <- c('CTR' = system.file("extdata",
                              "CTR_LR.csv",
                              package = "CrossTalkeR"),
          'EXP' = system.file("extdata",
                              "EXP_LR.csv",
                              package = "CrossTalkeR"))
output =  system.file("extdata", package = "CrossTalkeR")
genes <- c('TGFB1')
data <- generate_report(lrpaths = paths,
                       genes = genes,
                       out_path = paste0(output,'/'),
                       threshold = 0,
                         out_file = "report.html")
#> Create a Differential Table
#> Calculating CCI Ranking
#> EXP_x_CTR
#> 
#> Calculating GCI Ranking
#> EXP_x_CTR
#> Annotating the top Cell Genes
#> 'select()' returned 1:many mapping between keys and columns
#> 'select()' returned 1:many mapping between keys and columns
#> 'select()' returned 1:many mapping between keys and columns
#> 'select()' returned 1:many mapping between keys and columns
#> 'select()' returned 1:many mapping between keys and columns
#> 'select()' returned 1:many mapping between keys and columns
#> 'select()' returned 1:many mapping between keys and columns
#> 'select()' returned 1:many mapping between keys and columns
#> 'select()' returned 1:many mapping between keys and columns
#> 'select()' returned 1:many mapping between keys and columns
#> 'select()' returned 1:many mapping between keys and columns
#> 'select()' returned 1:many mapping between keys and columns
#> 'select()' returned 1:many mapping between keys and columns
#> 'select()' returned 1:many mapping between keys and columns
#> 'select()' returned 1:many mapping between keys and columns
#> 'select()' returned 1:many mapping between keys and columns
#> 'select()' returned 1:many mapping between keys and columns
#> 'select()' returned 1:many mapping between keys and columns
#> 'select()' returned 1:many mapping between keys and columns
#> 'select()' returned 1:many mapping between keys and columns
#> 'select()' returned 1:many mapping between keys and columns
#> 'select()' returned 1:many mapping between keys and columns
#> 'select()' returned 1:many mapping between keys and columns
#> 'select()' returned 1:many mapping between keys and columns
#> 'select()' returned 1:many mapping between keys and columns
#> 'select()' returned 1:many mapping between keys and columns
#> 'select()' returned 1:many mapping between keys and columns
#> 'select()' returned 1:many mapping between keys and columns
#> 'select()' returned 1:many mapping between keys and columns
#> 'select()' returned 1:many mapping between keys and columns
#> 'select()' returned 1:many mapping between keys and columns
#> 'select()' returned 1:many mapping between keys and columns
#> Adding missing grouping variables: `cellpair`
#> Adding missing grouping variables: `cellpair`
#> Network Analysis Done
#> Defining templates
#> Generating Report
#> Preparing Single Phenotype Report
#> Warning: ggrepel: 34 unlabeled data points (too many overlaps). Consider increasing max.overlaps
#> Warning: ggrepel: 33 unlabeled data points (too many overlaps). Consider increasing max.overlaps
#> Preparing Comparative Phenotype Report
#> Warning: ggrepel: 72 unlabeled data points (too many overlaps). Consider increasing max.overlaps
#> Report Done!
#> Analysis Complete