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Commit e6738bcc authored by Zhiyu Zhao's avatar Zhiyu Zhao
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Bug fixes.

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...@@ -12,9 +12,9 @@ This is an R program to visualize and analyze -omics data such as those from met ...@@ -12,9 +12,9 @@ This is an R program to visualize and analyze -omics data such as those from met
## How to run this tool: ## How to run this tool:
**Step 1:** Click on the download link https://cloud.biohpc.swmed.edu/index.php/s/nnq28yDTPwKFTNM (password: ODA@CRI_UTSW) to download a copy of the ODA tool. **Step 1:** Click on the download link https://cloud.biohpc.swmed.edu/index.php/s/nnq28yDTPwKFTNM (password: ODA@CRI_UTSW) to download a copy of the ODA tool. Downloading is NOT necessary for CRI users. The files are shared at /archive/CRI/shared/Tools/zzy/ODA on BioHPC.
**Step 2:** Make a copy of data template file from your ODA directory and open it in Excel. Read the instructions in there. This is your ***input file***. **Step 2:** Copy the data template file from your ODA directory, save it in your analysis folder, and open it in Excel. Read the instructions in there. This is your ***input file***.
**Step 3:** Copy your data table to the ***RawData*** sheet of your ***input file***. Data should be a table with samples, features, optional feature descriptions, and values. See data template for details. **Step 3:** Copy your data table to the ***RawData*** sheet of your ***input file***. Data should be a table with samples, features, optional feature descriptions, and values. See data template for details.
...@@ -22,15 +22,17 @@ This is an R program to visualize and analyze -omics data such as those from met ...@@ -22,15 +22,17 @@ This is an R program to visualize and analyze -omics data such as those from met
**Step 5:** Run the program with your ***input file*** and save results in an ***output folder***. If visualization is enabled, a Figures folder will be created to save the plots. If enrichment analysis is enabled, an EnrichmentAnalysis folder will be created to save the results. See below for ways of running the program. **Step 5:** Run the program with your ***input file*** and save results in an ***output folder***. If visualization is enabled, a Figures folder will be created to save the plots. If enrichment analysis is enabled, an EnrichmentAnalysis folder will be created to save the results. See below for ways of running the program.
1. Running on the BioHPC @ UTSW. Log on the BioHPC ***Portal***, launch a ***Web Visualization*** node, open a terminal from there, and run the following: 1. Running on the BioHPC @ UTSW. Log on the BioHPC ***Portal***, launch a ***Web Visualization*** node, open a ***terminal*** from there, and run the following:
``` ```
sh /path_to_the_program/oda_analysis.sh /input_path/your_data_file.xlsx /output_path/ optional_BioHPC_queue_name sh /path_to_the_program/oda_analysis.sh /input_path/your_data_file.xlsx /output_path/ optional_BioHPC_queue_name
or
sh /archive/CRI/shared/Tools/zzy/ODA/oda_analysis.sh /input_path/your_data_file.xlsx /output_path/ optional_BioHPC_queue_name #For CRI users only.
``` ```
2. Running on your local machine with a Singularity / Docker / Podman container. Make sure Singularity / Docker / Podman is installed and you can run it from a command line tool such as a Linux terminal or Windows CMD / PowerShell. If you do not use Singularity, you should request a copy of the corresponding Docker / Podman container from me. 2. Running on your local machine with a Singularity / Docker / Podman container. Make sure Singularity / Docker / Podman is installed and you can run it from a command line tool such as a Linux terminal or Windows CMD / PowerShell. If you do not use Singularity, you should request a copy of the corresponding Docker / Podman container from me.
``` ```
singularity exec /path_to_the_program/r_with_packages_4.3.2.sif Rscript /ODA/ODA.R /input_path/your_data_file.xlsx /output_path/ singularity exec /path_to_the_program/Vx.y/r_with_packages_4.3.2.sif Rscript /ODA/ODA.R /input_path/your_data_file.xlsx /output_path/
``` ```
3. Running on your local machine. Make sure R and required packages are installed and you can run the Rscript command from a command line tool such as a Linux terminal or Windows CMD / PowerShell. 3. Running on your local machine using R. Make sure R and required packages are installed and you can run the Rscript command from a command line tool such as a Linux terminal or Windows CMD / PowerShell. You should request a copy of the ODA source files from me.
``` ```
Rscript /path_to_the_program/ODA/ODA.R /input_path/your_data_file.xlsx /output_path/ Rscript /path_to_the_program/ODA/ODA.R /input_path/your_data_file.xlsx /output_path/
``` ```
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