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CrossTalker_install_basicusage.rmd
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CrossTalker_install_basicusage.rmd
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---
title: CrossTalkeR - Installation and Basic Execution
author:
- name: James S. Nagai
affiliation: Institute for Computational Genomics,
Faculty of Medicine,
RWTH Aachen University,
Aachen, 52074 Germany
- name: Nils B. Leimkühler
affiliation: Department of Hematology and Stem Cell Transplantation,
University Hospital Essen,
Germany
- name: Vanessa Klöker
affiliation: Institute for Computational Genomics,
Faculty of Medicine,
RWTH Aachen University,
Aachen, 52074 Germany
- name: Michael T. Schaub
affiliation:
- Department of Computer Science,
RWTH Aachen University,
Aachen, Germany
- name: Rebekka K. Schneider
affiliation:
- Department of Hematology,
Erasmus Medical Center,
Rotterdam, 3015GD,
the Netherlands
- Department of Cell Biology,
Institute for Biomedical Engineering,
Faculty of Medicine,
RWTH Aachen University,
Aachen, 52074 Germany
- Oncode Institute,
Erasmus Medical Center,
Rotterdam, 3015GD,
the Netherlands
- name: Ivan G. Costa
affiliation:
- Institute for Computational Genomics,
Faculty of Medicine,
RWTH Aachen University,
Aachen, 52074 Germany
output:
html_document
vignette: |
%\VignetteIndexEntry{CrossTalkeR-install-basicusage}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
---
# CrossTalkeR - Installation and Basic Execution
Here we like to give a short introduction on the installation and the basic usage of CrossTalkeR.
## Install
You can install and load the CrossTalkeR package with the simple commands below:
```{r, eval = FALSE}
install.packages("devtools")
devtools::install_github("https://github.com/CostaLab/CrossTalkeR", build_vignettes = TRUE)
require(CrossTalkeR)
```
There are the following possible system dependencies:
```{r, eval = FALSE}
libudunits2-dev
libgdal-dev
gdal-bin
libproj-dev
proj-data
proj-bin
libgeos-dev
```
## 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:
```{r, eval = FALSE}
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")
```
It is also possible to just perform the analysis part of CrossTalker, without generating the report:
```{r, eval = FALSE}
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")
```
A second 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.
```{r, eval = FALSE}
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")
```