Update README.md

README.md

@@ -1,32 +1,55 @@
 # Colabfold_batch Installer
 
-This repository contains a simplified method of installing [colabfold](https://github.com/sokrypton/ColabFold) for local UoD use, which is loosely based on [localcolabfold](https://github.com/YoshitakaMo/localcolabfold). Colabfold provides a greatly accelerated structure prediction compared to the 'traditional' alphafold approach by replacing the Hmmer/HHblits homology searches with a much faster MMSeqs2 based method - see [https://doi.org/10.1038/s41592-022-01488-1](https://doi.org/10.1038/s41592-022-01488-1). The localcolabfold installation does not work out of the box in our environment, so this is a streamlined installation which should produce a functional installation by running a single setup script.
+This repository contains a simplified method of installing [colabfold](https://github.com/sokrypton/ColabFold) for local UoD use, which is loosely based on [localcolabfold](https://github.com/YoshitakaMo/localcolabfold). Colabfold provides a greatly accelerated structure prediction compared to the 'traditional' alphafold approach by replacing the Hmmer/HHblits homology searches with a much faster MMSeqs2 based method - see [the colabfold paper](https://doi.org/10.1038/s41592-022-01488-1). The localcolabfold installation does not work out of the box in our environment, so this is a streamlined installation which should produce a functional installation by running a single setup script.
 
 ## Requirements
 
+### Singularity container
+
+* Nothing inparticular - The UoD HPC cluster provides Singularity access, including on CUDA-enabled GPU nodes appropriate for running colabfold. 
+
+This is temporarily available in `/cluster/gjb_lab/jabbott/singularity` until a better home can be found for it...
+
+### Full Installation
 *  Anaconda/Miniconda3/Mamba installation. The installation script will preferentially use mamba to carry out the installation, but will fallback to conda if this is not available. If you don't already have a conda installation, see [The Cluster Wiki](https://teams.microsoft.com/l/channel/19%3A63a2d1d10e5346c79d8b35dec6006a40%40thread.tacv2/tab%3A%3A8ac3086d-c08d-426b-9140-4890bb613c19?groupId=4153042c-375d-4caa-a654-d691f65da8bb&tenantId=ae323139-093a-4d2a-81a6-5d334bcd9019&allowXTenantAccess=false) for instructions on setting this up.
 *  Approximately 14 Gb free disk space. This is mostly required for storing the alphafold weights
 *  git (optional)
 
 ## Installation
 
+### Singularity
+
+All necessary components are already available on the cluster. 
+
+### Full Installation
+
 1. Obtain a copy of this repository either using git i.e.  
 `git clone git://github.com/bartongroup/JCA_colabfold_batch.git`  
 or by downloading a release tarball from the link on the right under 'Releases'. Copy this tarball onto the cluster filesystem and extract with  
-`tar zxvf v1.5.2-beta1.tar.gz`
+`tar zxvf v1.5.2-beta2.tar.gz`
 
 2. Change into the directory which is created by step 1 - this will have the repository name if cloned from git, or the version number if obtained from a Release tarball.
 a)  From a repository clone:  
 `cd Colabfold_batch_installer`  
 b) From a release tarball:  
-`cd Colabfold_batch_installer-1.5.2-beta1`
+`cd Colabfold_batch_installer-1.5.2-beta2`
 
 3. Run the setup script:  
 `./setup.sh`  
 This will create a new conda environment named `colabfold_batch` based upon the definition within the `colabfold_batch.yaml` file. Alphafold weights are then downloaded into the `$CONDA_PREFIX/share/colabfold` directory within the conda environment. The installation will take approximately 15 minutes to complete. 
 
 ## Usage
 
+### Singularity
+
+Usage: run_colabfold_singularity.sh -i /path/to/fasta/file [-c 'colabfold arguments']
+
+The `run_colabfold_singularity.sh` script can be submitted directly to GridEngine, and requires at a minimun the path to an input fasta file. Any specific colabfold arguments can be provided using the `-c` argument. Log files will be written to a 'colabfold_logs' directory in the submission directory, while outputs will be written to a `colabfold_outputs` directory within the directory containing the submitted fasta file. 
+
+i.e. `qsub /path/to/run_colabfold.sh -i test/cadh5_arath.fa -c "--num-recycle 5 --amber --num-relax 5"`  
+
+### Full Installation
+
  Activate the `colabfold_batch` environment  
 `conda activate colabfold_batch`