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Interface to R

sumanth edited this page Jun 30, 2021 · 5 revisions

11 Interface to R

Users can execute their own R scripts using MOG. This allows access to numerous statistical libraries which R has. The user need to write their R scripts to use data from MOG. MOG provides a convenient way for users to select relevant features and samples and forward this data to an R script. The R script makes use of this API and uses the input data to perform the computations or visualizations. The R path can be set via MOG properties. See Section 12.2.

11.1 R script format

This section explains how to write an R script to be executed with MOG. To execute an R script from MOG, the R script should take following arguments:

  1. The first argument is that the path to the "data file" which is generated by MOG and stored in the project's directory. This file is a tab-delimited file. The file contains feature as rows and samples as columns.
  2. The second argument is the path to the "metadata file" which is the metadata file used in the MOG project.
  3. The third argument is the path to the output directory. When executing an R script, MOG asks an output directory name which is created under the project directory. Using this path all output from R could be saved under this directory. Example scripts are available at: https://github.com/urmi-21/MetaOmGraph/tree/master/rscripts

Overview

1. Introduction

2. THE BASICS: Downloading and Using MOG

3. Open a Project

4. The Main MOG GUI

5. Sort, subset, transform, analyze, and reorder the Data

6. Coexpression Analysis

7. Visualizations

8. Differential Expression Analysis

9. Dimensionality Reduction

10. Create Your Own Projects

11. Interface to R

12. Change Project Properties and MOG Properties

13. Reproducibility

1. Introduction

1.1 Introduction

1.2 How to use this guide

1.3 Citation

1.4 License

1.5 Glossary

2. The BASICS

2.1 System Requirements

2.2 Download MOG

2.3 Download a pre-compiled project

2.4 Start MetaOmGraph

2.5 Run MetaOmGraph by providing more memory(RAM)

2.6 Troubleshooting

3. Open a Project

3.1 Open a project

4. The Main MOG GUI

4.1 Save a current project

4.2 Open an existing project

5. Sort, Subset, transform, analyze, and reorder the Data

5.1 Choosing the Replicate Column

5.2 Transform Data

5.3 Feature Lists

5.4 Sample Lists

5.5 Search or Filter Sample MetaData

6. Coexpression Analysis

6.1 Correlation Between Features

6.2 Correlation Matrices

6.3 Correlation Betweeen Samples

7. Visualization

7.1 Line Charts

7.2 Line Charts with Averaged Replicates

7.3 Scatter Plot

7.4 Box Plot

7.5 Histogram

7.6 Volcano Plot

7.7 Correlation Histogram

8. Differential Expression Analysis

8.1 Differential Expression Analysis Window

8.2 Differential Expression Results Window

9. Dimensionality Reduction

9.1 Principal component analysis (PCA)

9.2 t-distributed stochastic neighbor embedding (t-SNE)

10. Create Your Own Projects

10.1 Input format

10.2 Start a new project

11. Interface to R

11.1 R script Format

12. Change Project Properties and MOG Properties

12.1 Projects Properties

12.2 MOG properties

13. Reproducibility

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