CrossTalkeR - Basic Usage

James S. Nagai

Institute for Computational Genomics, Faculty of Medicine, RWTH Aachen University, Aachen, 52074 Germany

Nils B. Leimkühler

Department of Hematology and Stem Cell Transplantation, University Hospital Essen, Germany

Vanessa Klöker

Institute for Computational Genomics, Faculty of Medicine, RWTH Aachen University, Aachen, 52074 Germany

Michael T. Schaub

Department of Computer Science, RWTH Aachen University, Aachen, Germany

Rebekka K. Schneider

Department of Hematology, Erasmus Medical Center, Rotterdam, 3015GD, the NetherlandsDepartment of Cell Biology, Institute for Biomedical Engineering, Faculty of Medicine, RWTH Aachen University, Aachen, 52074 GermanyOncode Institute, Erasmus Medical Center, Rotterdam, 3015GD, the Netherlands

Ivan G. Costa

Institute for Computational Genomics, Faculty of Medicine, RWTH Aachen University, Aachen, 52074 Germany

CrossTalkeR - Basic Execution

Here we like to give a short introduction on the basic usage of CrossTalkeR.

Basic Execution

Here we show the most basic way to execute CrossTalkeR. All you need to provide are the paths to the ligand-receptor interaction analysis results and a path to save the results to:

library(CrossTalkeR)

paths <- c('Condition1' = "/path/to/condition1/LR-interactions.csv",
           'Condition2' = "/path/to/condition2/LR-interactions.csv")

output <- "/path/to/output/folder/"
data <- generate_report(paths,
                out_path=output,
                out_file = 'vignettes_example.html',
                output_fmt = "html_document",
                report = TRUE,
                org = "hsa", 
                filtered_net=TRUE)

In case the tables are already obtained inside your R session, one can use the following approach(This also apply for the functions below).

obj1 <- "a condition1 data frame object"
obj2 <- "a condition2 data frame object"

paths <- list('Condition1' = obj1,
           'Condition2' = obj2)

output <- "/path/to/output/folder/"
data <- generate_report(paths,
                out_path=output,
                out_file = 'vignettes_example.html',
                output_fmt = "html_document",
                report = TRUE,
                org = "hsa", 
                filtered_net=TRUE)

Performing only the analysis

To just perform the analysis part of CrossTalker, without generating the report:

library(CrossTalkeR)

paths <- c('Condition1' = "/path/to/condition1/LR-interactions.csv",
           'Condition2' = "/path/to/condition2/LR-interactions.csv")

output <- "/path/to/output/folder/"
data <- analise_LR(paths,
                out_path=output,
                org = "hsa" 
                filtered_net=TRUE)

Getting Report from an existing project

An addictional possibility is to generate the reports from existing CrossTalkeR objects. In this case the out_path should point to the folder with the ‘LR_data_final.Rds’ file.

library(CrossTalkeR)

output <- "/path/to/output/folder/"
data <- make_report(out_path=output,
                out_file = 'vignettes_example.html',
                output_fmt = "html_document",
                report = TRUE,
                org = "hsa" 
                filtered_net=TRUE)