Merge pull request #125 from torres-alexis/DEV_GeneLab_Reference_Anno…

…tations_vGL-DPPD-7110-A [GL_RefAnnotTable] Installation updates
nasa · Oct 22, 2024 · 0338c93 · 0338c93
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diff --git a/GeneLab_Reference_Annotations/Workflow_Documentation/GL_RefAnnotTable-A/README.md b/GeneLab_Reference_Annotations/Workflow_Documentation/GL_RefAnnotTable-A/README.md
@@ -1,155 +1,195 @@
-# GL_RefAnnotTable Workflow Information and Usage Instructions
+# GL_RefAnnotTable-A Workflow Information and Usage Instructions <!-- omit in toc -->
 
-## General workflow info
-The current GeneLab Reference Annotation Table (GL_RefAnnotTable-A) pipeline is implemented as an R workflow that can be run from a command line interface (CLI) using bash. The workflow can be used even if you are unfamiliar with R, but if you want to learn more about R, visit the [R-project about page here](https://www.r-project.org/about.html). Additionally, an introduction to R along with installation help and information about using R for bioinformatics can be found [here at Happy Belly Bioinformatics](https://astrobiomike.github.io/R/basics).  
+## Table of Contents <!-- omit in toc -->
 
-## Utilizing the workflow
+- [General Workflow Information](#general-workflow-information)
+- [Utilizing the Workflow](#utilizing-the-workflow)
+  - [1. Download the Workflow Files](#1-download-the-workflow-files)
+  - [2. Run the Workflow](#2-run-the-workflow)
+    - [Approach 1: Using Singularity](#approach-1-using-singularity)
+      - [Step 1: Install Singularity](#step-1-install-singularity)
+      - [Step 2: Fetch the Singularity Image](#step-2-fetch-the-singularity-image)
+      - [Step 3: Run the Workflow](#step-3-run-the-workflow)
+      - [Step 4: Run the Annotations Database Creation Function as a Stand-Alone Script](#step-4-run-the-annotations-database-creation-function-as-a-stand-alone-script)
+    - [Approach 2: Using a Local R Environment](#approach-2-using-a-local-r-environment)
+      - [Step 1: Install R and Required R Packages](#step-1-install-r-and-required-r-packages)
+      - [Step 2: Run the Workflow](#step-2-run-the-workflow)
+      - [Step 3: Run the Annotations Database Creation Function as a Stand-Alone Script](#step-3-run-the-annotations-database-creation-function-as-a-stand-alone-script)
 
-1. [Install R and R packages](#1-install-r-and-r-packages)  
-2. [Download the workflow files](#2-download-the-workflow-files)  
-3. [Setup Execution Permission for Workflow Scripts](#3-setup-execution-permission-for-workflow-scripts)
-4. [Run the workflow](#4-run-the-workflow)  
-5. [Run the annotations database creation function as a stand-alone script](#5-run-the-annotations-database-creation-function-as-a-stand-alone-script)
-6. [Run the Workflow Using Docker or Singularity](#6-run-the-workflow-using-docker-or-singularity)
-<br>
+---
 
-### 1. Install R and R packages
+## General Workflow Information
 
-We recommend installing R via the [Comprehensive R Archive Network (CRAN)](https://cran.r-project.org/) as follows: 
+The current GeneLab Reference Annotation Table (GL_RefAnnotTable-A) pipeline is implemented as an R workflow that can be run from a command line interface (CLI) using bash. The workflow can be executed using either a Singularity container or a local R environment. The workflow can be used even if you are unfamiliar with R, but if you want to learn more about R, visit the [R-project about page here](https://www.r-project.org/about.html). Additionally, an introduction to R along with installation help and information about using R for bioinformatics can be found [here at Happy Belly Bioinformatics](https://astrobiomike.github.io/R/basics).
 
-1. Select the [CRAN Mirror](https://cran.r-project.org/mirrors.html) closest to your location.
-2. Click the link under the "Download and Install R" section that's consistent with your machine.
-3. Click on the R-4.4.0 package consistent with your machine to download.
-4. Double click on the R-4.4.0.pkg downloaded in step 3 and follow the installation instructions.
+---
+
+## Utilizing the Workflow
+
+To utilize the GL_RefAnnotTable-A workflow, follow the instructions below to download the necessary workflow files. Once downloaded, the workflow can be executed using two approaches:
+
+1. **[Using Singularity](#approach-1-using-singularity)**
+2. **[Using a Local R Environment](#approach-2-using-a-local-r-environment)**
+
+Please follow the instructions for the approach that best matches your setup and preferences. Each method is explained in detail below.
 
-Once R is installed, open a CLI terminal and run the following command to activate R:
+---
+
+### 1. Download the Workflow Files
+
+Download the latest version of the GL_RefAnnotTable-A workflow:
 
 ```bash
-R
+curl -LO https://github.com/nasa/GeneLab_Data_Processing/releases/download/GL_RefAnnotTable-A_1.1.0/GL_RefAnnotTable-A_1.1.0.zip
+unzip GL_RefAnnotTable-A_1.1.0.zip
 ```
-`
-Within an active R environment, run the following commands to install the required R packages:
 
-```R
-install.packages("tidyverse")
+---
 
-install.packages("BiocManager")
+### 2. Run the Workflow
 
-BiocManager::install("STRINGdb")
-BiocManager::install("PANTHER.db")
-BiocManager::install("rtracklayer")
-BiocManager::install("AnnotationForge")
-BiocManager::install("biomaRt")
-BiocManager::install("GO.db")
-```
+The GL_RefAnnotTable-A workflow can be run using two approaches:
 
-<br>
+- **[Approach 1: Using Singularity](#approach-1-using-singularity)**
+- **[Approach 2: Using a Local R Environment](#approach-2-using-a-local-r-environment)**
 
-### 2. Download the Workflow Files
+---
 
-All files required for utilizing the GL_RefAnnotTable-A workflow for generating reference annotation tables are in the [workflow_code](workflow_code) directory. To get a copy of latest GL_RefAnnotTable version on to your system, run the following command:
+#### Approach 1: Using Singularity
 
-```bash
-curl -LO https://github.com/nasa/GeneLab_Data_Processing/releases/download/GL_RefAnnotTable-A_1.1.0/GL_RefAnnotTable-A_1.1.0.zip
-``` 
+This approach allows you to run the workflow within a containerized environment, ensuring consistency and reproducibility.
+
+##### Step 1: Install Singularity
+
+Singularity is a containerization platform for running applications portably and reproducibly. We use container images hosted on Quay.io to encapsulate all the necessary software and dependencies required by the GL_RefAnnotTable-A workflow. This setup allows you to run the workflow without installing any software directly on your system. Other containerization tools like Docker or Apptainer can also be used to pull and run these images.
+
+We recommend installing Singularity system-wide as per the official [Singularity installation documentation](https://docs.sylabs.io/guides/3.10/admin-guide/admin_quickstart.html).
+
+> **Note**: While Singularity is also available through [Anaconda](https://anaconda.org/conda-forge/singularity), we recommend installing Singularity system-wide following the official installation documentation.
 
-<br>
+##### Step 2: Fetch the Singularity Image
 
-### 3. Setup Execution Permission for Workflow Scripts
+To pull the Singularity image needed for the workflow, you can use the provided script as directed below or pull the image directly.
 
-Once you've downloaded the GL_RefAnnotTable-A workflow directory as a zip file, unzip the workflow then `cd` into the GL_RefAnnotTable-A_1.1.0 directory on the CLI. Next, run the following command to set the execution permissions for the R script:
+> **Note**: This command should be run in the location containing the `GL_RefAnnotTable-A_1.1.0` directory that was downloaded in [step 1](#1-download-the-workflow-files). Depending on your network speed, fetching the images will take approximately 20 minutes.
 
 ```bash
-unzip GL_RefAnnotTable-A_1.1.0.zip
-cd GL_RefAnnotTable-A_1.1.0
-chmod -R u+x *R
+bash GL_RefAnnotTable-A_1.1.0/bin/prepull_singularity.sh GL_RefAnnotTable-A_1.1.0/config/software/by_docker_image.config
 ```
 
-<br>
+Once complete, a `singularity` folder containing the Singularity images will be created. Run the following command to export this folder as an environment variable:
+
+```bash
+export SINGULARITY_CACHEDIR=$(pwd)/singularity
+```
 
-### 4. Run the Workflow
+##### Step 3: Run the Workflow
 
-While in the GL_RefAnnotTable workflow directory, you are now able to run the workflow. Below is an example of how to run the workflow to build an annotation table for Mus musculus (mouse):
+While in the directory containing the `GL_RefAnnotTable-A_1.1.0` folder, you can now run the workflow. Below is an example for generating the annotation table for *Mus musculus* (mouse):
 
 ```bash
-Rscript GL-DPPD-7110-A_build-genome-annots-tab.R 'Mus musculus'
+singularity exec -B $(pwd)/GL_RefAnnotTable-A_1.1.0:/work \
+$SINGULARITY_CACHEDIR/quay.io-nasa_genelab-gl-refannottable-a-1.1.0.img \
+Rscript /work/GL-DPPD-7110-A_build-genome-annots-tab.R 'Mus musculus'
 ```
 
 **Input data:**
 
 - No input files are required. Specify the target organism using a positional command line argument. `Mus musculus` is used in the example above. To see a list of all available organisms, run `Rscript GL-DPPD-7110-A_build-genome-annots-tab.R` without positional arguments. The correct argument for each organism can also be found in the 'species' column of the [GL-DPPD-7110-A_annotations.csv](../../Pipeline_GL-DPPD-7110_Versions/GL-DPPD-7110-A/GL-DPPD-7110-A_annotations.csv)
-
 - Optional: a reference table CSV can be supplied as a second positional argument instead of using the default [GL-DPPD-7110-A_annotations.csv](../../Pipeline_GL-DPPD-7110_Versions/GL-DPPD-7110-A/GL-DPPD-7110-A_annotations.csv)
 
 **Output data:**
 
 - *-GL-annotations.tsv (Tab delineated table of gene annotations)
 - *-GL-build-info.txt (Text file containing information used to create the annotation table, including tool and tool versions and date of creation)
 
-### 5. Run the annotations database creation function as a stand-alone script
+##### Step 4: Run the Annotations Database Creation Function as a Stand-Alone Script
 
-When the workflow is run, if the reference table does not specify an annotations database for the target_organism in the `annotations` column, the `install_annotations` function, defined in the `install-org-db.R` script, will be executed. This script will locally create and install an annotations database R package using AnnotationForge. This function can also be run as a stand-alone script from the command line:
+If the reference table does not specify an annotations database for the target organism in the 'annotations' column, the `install_annotations` function (defined in `install-org-db.R`) will be executed. This function can also be run as a stand-alone script:
 
 ```bash
-Rscript install-org-db.R 'Bacillus subtilis' /path/to/GL-DPPD-7110-A_annotations.csv
+singularity exec -B $(pwd)/GL_RefAnnotTable-A_1.1.0:/work \
+$SINGULARITY_CACHEDIR/quay.io-nasa_genelab-gl-refannottable-a-1.1.0.img \
+Rscript /work/install-org-db.R 'Bacillus subtilis'
 ```
 
 **Input data:**
 
-- The target organism must be specified as the first positional command line argument, `Bacillus subtilis` is used in the example above. The correct argument for each organism can be found in the 'species' column of the [GL-DPPD-7110-A_annotations.csv](../../Pipeline_GL-DPPD-7110_Versions/GL-DPPD-7110-A/GL-DPPD-7110-A_annotations.csv)
-
-- The path to a local reference table must also be supplied as the second positional argument
+- The target organism must be specified as the first positional command line argument. `Bacillus subtilis` is used in the example above. The correct argument for each organism can be found in the 'species' column of [GL-DPPD-7110-A_annotations.csv](https://raw.githubusercontent.com/nasa/GeneLab_Data_Processing/master/GeneLab_Reference_Annotations/Pipeline_GL-DPPD-7110_Versions/GL-DPPD-7110-A/GL-DPPD-7110-A_annotations.csv)
+- Optional: A local reference table can be supplied as a second positional argument. If not provided, the script will download the current version of GL-DPPD-7110-A_annotations.csv from Github by default.
 
 **Output data:**
 
-- org.*.eg.db/ (species-specific annotation database, as a local R package)
+- org.*.eg.db/ (Species-specific annotation database, as a local R package)
 
-### 6. Run the Workflow Using Docker or Singularity
+---
 
-Rather than running the workflow in your local environment, you can use a Docker or Singularity container. This method ensures that all dependencies are correctly installed.
+#### Approach 2: Using a Local R Environment
 
-1. **Pull the container image:**
+This approach allows you to run the workflow directly in your local R environment without using containers.
 
-   Docker:
-   ```bash
-   docker pull quay.io/nasa_genelab/gl-refannottable:v1.0.0
-   ```
+##### Step 1: Install R and Required R Packages
 
-   Singularity:
-   ```bash
-   singularity pull docker://quay.io/nasa_genelab/gl-refannottable:v1.0.0
-   ```
+We recommend installing R via the [Comprehensive R Archive Network (CRAN)](https://cran.r-project.org/):
 
-2. **Download the workflow files:**
+1. Select the [CRAN Mirror](https://cran.r-project.org/mirrors.html) closest to your location.
+2. Navigate to the download page for your operating system.
+3. Download and install R (e.g., R-4.4.0).
 
-   ```bash
-   curl -LO https://github.com/nasa/GeneLab_Data_Processing/releases/download/GL_RefAnnotTable-A_1.1.0/GL_RefAnnotTable-A_1.1.0.zip
-   unzip GL_RefAnnotTable-A_1.1.0.zip
-   ```
+Once R is installed, you need to install the required R packages.
 
-3. **Run the workflow:**
+Open a terminal and start R:
 
-   Docker:
-   ```bash
-   docker run -it -v $(pwd)/GL_RefAnnotTable-A_1.1.0:/work \
-     quay.io/nasa_genelab/gl-refannottable:v1.0.0 \
-     bash -c "cd /work && Rscript GL-DPPD-7110-A_build-genome-annots-tab.R 'Mus musculus'"
-   ```
+```bash
+R
+```
 
-   Singularity:
-   ```bash
-   singularity exec -B $(pwd)/GL_RefAnnotTable-A_1.1.0:/work \
-     gl-refannottable_v1.0.0.sif \
-     bash -c "cd /work && Rscript GL-DPPD-7110-A_build-genome-annots-tab.R 'Mus musculus'"
-   ```
+Within the R environment, run the following commands to install the required packages:
+
+```R
+install.packages("tidyverse")
+install.packages("BiocManager")
+BiocManager::install("STRINGdb")
+BiocManager::install("PANTHER.db")
+BiocManager::install("rtracklayer")
+BiocManager::install("AnnotationForge")
+BiocManager::install("biomaRt")
+BiocManager::install("GO.db")
+```
+
+##### Step 2: Run the Workflow
+
+While in the directory containing the `GL_RefAnnotTable-A_1.1.0` folder, you can now run the workflow. Below is an example of how to run the workflow to build an annotation table for *Mus musculus* (mouse):
+
+```bash
+Rscript GL_RefAnnotTable-A_1.1.0/GL-DPPD-7110-A_build-genome-annots-tab.R 'Mus musculus'
+```
 
 **Input data:**
 
 - No input files are required. Specify the target organism using a positional command line argument. `Mus musculus` is used in the example above. To see a list of all available organisms, run `Rscript GL-DPPD-7110-A_build-genome-annots-tab.R` without positional arguments. The correct argument for each organism can also be found in the 'species' column of the [GL-DPPD-7110-A_annotations.csv](../../Pipeline_GL-DPPD-7110_Versions/GL-DPPD-7110-A/GL-DPPD-7110-A_annotations.csv)
-
 - Optional: a reference table CSV can be supplied as a second positional argument instead of using the default [GL-DPPD-7110-A_annotations.csv](../../Pipeline_GL-DPPD-7110_Versions/GL-DPPD-7110-A/GL-DPPD-7110-A_annotations.csv)
 
 **Output data:**
 
 - *-GL-annotations.tsv (Tab delineated table of gene annotations)
 - *-GL-build-info.txt (Text file containing information used to create the annotation table, including tool and tool versions and date of creation)
+
+##### Step 3: Run the Annotations Database Creation Function as a Stand-Alone Script
+
+If the reference table does not specify an annotations database for the target organism in the 'annotations' column, the `install_annotations` function (defined in `install-org-db.R`) will be executed. This function can also be run as a stand-alone script:
+
+```bash
+Rscript GL_RefAnnotTable-A_1.1.0/install-org-db.R 'Bacillus subtilis'
+```
+
+**Input data:**
+
+- The target organism must be specified as the first positional command line argument. `Bacillus subtilis` is used in the example above. The correct argument for each organism can be found in the 'species' column of [GL-DPPD-7110-A_annotations.csv](https://raw.githubusercontent.com/nasa/GeneLab_Data_Processing/master/GeneLab_Reference_Annotations/Pipeline_GL-DPPD-7110_Versions/GL-DPPD-7110-A/GL-DPPD-7110-A_annotations.csv)
+- Optional: A local reference table can be supplied as a second positional argument. If not provided, the script will download the current version of GL-DPPD-7110-A_annotations.csv from Github by default.
+
+**Output data:**
+
+- org.*.eg.db/ (species-specific annotation database, as a local R package)
+
+---
diff --git a/...ations/Workflow_Documentation/GL_RefAnnotTable-A/workflow_code/bin/prepull_singularity.sh b/...ations/Workflow_Documentation/GL_RefAnnotTable-A/workflow_code/bin/prepull_singularity.sh
@@ -0,0 +1,32 @@
+
+#!/usr/bin/env bash
+
+# Addresses issue: https://github.com/nextflow-io/nextflow/issues/1210
+
+CONFILE=${1:-nextflow.config}
+OUTDIR=${2:-./singularity}
+
+if [ ! -e $CONFILE ]; then
+        echo "$CONFILE does not exist"
+        exit
+fi
+
+TMPFILE=`mktemp`
+
+CURDIR=$(pwd)
+
+mkdir -p $OUTDIR
+
+cat ${CONFILE}|grep 'container'|perl -lane 'if ( $_=~/container\s*\=\s*\"(\S+)\"/ ) { $_=~/container\s*\=\s*\"(\S+)\"/; print $1 unless ( $1=~/^\s*$/ or $1=~/\.sif/ or $1=~/\.img/ ) ; }' > $TMPFILE
+
+cd ${OUTDIR}
+
+while IFS= read -r line; do
+        name=$line
+        name=${name/:/-}
+        name=${name//\//-}
+        echo $name
+        singularity pull ${name}.img docker://$line
+done < $TMPFILE
+
+cd $CURDIR
diff --git a/...low_Documentation/GL_RefAnnotTable-A/workflow_code/config/software/by_docker_image.config b/...low_Documentation/GL_RefAnnotTable-A/workflow_code/config/software/by_docker_image.config
@@ -0,0 +1,6 @@
+// Config that specifies containers for nextflow processes 
+process {
+    withName: 'GL_REFANNOTTABLE_A' {
+        container = "quay.io/nasa_genelab/gl-refannottable-a:1.1.0"
+    }
+}
diff --git a/...ence_Annotations/Workflow_Documentation/GL_RefAnnotTable-A/workflow_code/install-org-db.R b/...ence_Annotations/Workflow_Documentation/GL_RefAnnotTable-A/workflow_code/install-org-db.R
@@ -1,14 +1,31 @@
 # install-org-db.R
 
+# Set R library path to current working directory
+lib_path <- file.path(getwd())
+.libPaths(lib_path)
+
+# Load required libraries
+library(tidyverse)
+library(AnnotationForge)
+library(BiocManager)
+
 # Function: Get annotations db from ref table. If no annotations db is defined, create the package name from genus, species, (and strain for microbes), 
 # Try to Bioconductor install annotations db. If fail then build the package using AnnotationForge, install it into the current directory.
 # Requires ~80GB for NCBIFilesDir file caching
-install_annotations <- function(target_organism, refTablePath) {
-    if (!file.exists(refTablePath)) {
-        stop("Reference table file does not exist at the specified path: ", refTablePath)
-    }
+install_annotations <- function(target_organism, refTablePath = NULL) {
+    # Default URL for the specific version of the reference CSV
+    default_url <- "https://raw.githubusercontent.com/nasa/GeneLab_Data_Processing/master/GeneLab_Reference_Annotations/Pipeline_GL-DPPD-7110_Versions/GL-DPPD-7110-A/GL-DPPD-7110-A_annotations.csv"
+
+    # Use the provided path if available, otherwise use the default URL
+    csv_source <- ifelse(is.null(refTablePath), default_url, refTablePath)
+
+    # Attempt to read the CSV file
+    ref_table <- tryCatch({
+        read.csv(csv_source)
+    }, error = function(e) {
+        stop("Failed to read the reference table: ", e$message)
+    })
 
-    ref_table <- read.csv(refTablePath)
     target_taxid <- ref_table %>%
         filter(species == target_organism) %>%
         pull(taxon)
@@ -52,6 +69,7 @@ install_annotations <- function(target_organism, refTablePath) {
     } else {
         cat(paste0("\nAttempting to install '", target_org_db, "' from Bioconductor...\n"))
         BiocManager::install(target_org_db, ask = FALSE)
+
         if (requireNamespace(target_org_db, quietly = TRUE)) {
             cat(paste0("'", target_org_db, "' has been successfully installed from Bioconductor.\n"))
         } else {
@@ -85,3 +103,17 @@ install_annotations <- function(target_organism, refTablePath) {
     cat(paste0("Using Annotation Database '", target_org_db, "'.\n"))
     return(target_org_db)
 }
+
+if (!interactive()) {
+  # Parse command line arguments
+  args <- commandArgs(trailingOnly = TRUE)
+
+  if (length(args) < 1) {
+    stop("Usage: Rscript install-org-db.R <target_organism> [refTablePath]")
+  }
+
+  target_organism <- args[1]
+  refTablePath <- if (length(args) > 1) args[2] else NULL
+
+  install_annotations(target_organism, refTablePath)
+}