This function do a CCI plot
Usage
plot_cci(
graph,
colors,
plt_name,
coords,
emax = NULL,
leg = FALSE,
low = 25,
high = 75,
ignore_alpha = FALSE,
log = FALSE,
efactor = 8,
vfactor = 12,
vnames = T,
pg = NULL
)
Arguments
- graph
Paths of single condition LR data
- colors
Cell type (Cluster) Colors
- plt_name
Plot Name (Title)
- coords
object coordinates
- emax
Max MeanLR across the all inputs, if its not defined, the method going to consider the max find within a sample
- leg
Set color legend
- low
Lower threshold: This parameter low and high defines the edges
- high
Higher threshould which will be filtered. Edges within the interval [low\,high] are filtered.
- ignore_alpha
not include transparency on the plot
- log
logscale the interactions
- efactor
edge scale factor
- vfactor
edge scale factor
- vnames
remove vertex labels
- pg
pagerank values
Examples
paths <- c('CTR' = system.file("extdata",
"CTR_LR.csv",
package = "CrossTalkeR"),
'EXP' = system.file("extdata",
"EXP_LR.csv",
package = "CrossTalkeR"))
genes <- c('TGFB1')
output = system.file("extdata", package = "CrossTalkeR")
data <- generate_report(paths,
genes,
out_path=paste0(output,'/'),
threshold=0,
out_file = 'vignettes_example.html',
output_fmt = "html_document",
report = FALSE)
#> 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
#> Analysis Complete
plot_cci(graph = data@graphs$CTR,
colors = data@colors,
plt_name = 'Example 1',
coords = data@coords[igraph::V(data@graphs$CTR)$name,],
emax = NULL,
leg = FALSE,
low = 0,
high = 0,
ignore_alpha = FALSE,
log = FALSE,
efactor = 8,
vfactor = 12,
vnames = TRUE)