https://github.com/cerdem12/sparced-legacy

SPARCED model creation and simulation package

https://github.com/cerdem12/sparced-legacy

Repository

SPARCED model creation and simulation package

https://github.com/cerdem12/SPARCED-legacy/blob/master/

# SPARCED

SPARCED is a simple and efficient pipeline for construction, merging, expansion, and simulation of large-scale, single-cell mechanistic models. With minimal set-up, users can configure the model for parallel runs on a Kubernetes cluster (SPARCED-nf), or small-scale experiments on their local machine (SPARCED-jupyter). More information on the model itself can be found [here](https://www.biorxiv.org/content/10.1101/2020.11.09.373407v1.full).


## Dependencies

- [Docker](https://docs.docker.com/get-docker/)
- [Nextflow](https://www.nextflow.io/docs/latest/getstarted.html) *(Optional: SPARCED-nf requirement only)*
- [kubectl](https://kubernetes.io/docs/tasks/tools/install-kubectl/) *(Optional: SPARCED-nf requirement only)* 

## Instructions
### Setting up your environment

1. Clone this repository from the command-line using `git clone --recursive https://github.com/birtwistlelab/SPARCED.git`
2. Make sure the dependencies listed above are installed
3. (SPARCED-nf only) Ensure you have a Kubernetes `config` file for your chosen cluster located in your `~/.kube` folder

### SPARCED-nf

#### Setting up the model

1. Edit the files in the `input_files` folder as needed. These values will be built into the *creation* of the model. For editing the values present for the model's *simulation*, see the directions accompanying the configuration step.
2. Use `./kube-runner/kube-load.sh  input_files` to load your input data to the PVC of the kube cluster. `kube-load.sh` assumes a `/workspaces` folder as the base of the PVC, and saves this input data at the path `/workspaces/$USER/input_files/`.  __Important__: Before every run where you plan on uploading new data to the PVC, it's important that you run `./kube-runner/kube-login.sh ` and delete the currently existing `/workspaces/$USER/input_files/` folder. If not, you run the risk of your model selecting the wrong files.
3. Edit the values in the `kube-nextflow.config` file in the `configs` folder (for help, see the config README [here](https://github.com/birtwistlelab/SPARCED/blob/master/configs/README.md))

#### Executing the workflow

1. Starting the workflow: 
    - `nextflow kuberun birtwistlelab/SPARCED -v  -c configs/kube-nextflow.config`
2. Retrieving data
    - After the run is finished, save your data from the PVC down to your local machine with `./kube-runner/kube-save.sh  ` (`kube-save.sh` will find your `work directory` path as relative to your `workspace/$USER` directory in the PVC. So with the default configurations, it should just be `work`)

#### Final SPARCED-nf notes

- For problems, feel free to consult our [troubleshooting guide](https://github.com/birtwistlelab/SPARCED/blob/master/TROUBLESHOOTING.md) or create issue requests. 
- For brave souls with a lot of local computer power but no Kubernetes cluster, SPARCED-nf is also built to be able to run locally. Simply launch with `nextflow run` instead of `kuberun` and work from the `configs/local-nextflow.config` template.

### SPARCED-jupyter

#### Setup
Once you have Docker installed, follow the simple steps below.

1. In a terminal window, use the command `docker login` with your account credentials. If you don't have an account yet, head over to hub.docker.com to set one up.
2. Use `docker pull birtwistlelab/sparced-notebook:latest` to download the latest version of the docker image
3. Once the download is complete, use `docker run -p 8888:8888 --name testnb1 -i -t birtwistlelab/sparced-notebook:latest`, and in your browser, go to the last URL produced in your terminal from this command
    - N.B. `testnb1` is just a sample name for the container you're creating with this command. If you try to create another container with this name, delete the old one first with `docker rm testnb1`
4. Viola! Once this command finishes, you should see a URL in your terminal that looks similar to `http://127.0.0.1:8888/?token=4a7c71c7a3b0080a4f331b256ae435fbc70`--paste this into your browser. You can now begin stepping through the commands in each of the files in the `jupyter_notebooks` folder to learn more about the model and perform small runs.

To use custom data in the SPARCED-jupyter workflow, start a container with the commands above, and look at the `input_files` directory. Delete the current files and run `docker cp  :/app/input_files/` to replace them.

### SPARCED_Brep

Files to exactly replicate Bouhaddou2018 model. In this format, mRNAs and protein species are tracked in separate variables. The number of species and ratelaws are also the same Bouhaddou2018 model. SPARCED is the new, updated, and cleaned up version.

## Acknowledgements:

SPARCED is a product of [Birtwistle Lab](http://www.birtwistlelab.com/) and we greatly appreciate the help from multiple colloborators, including [Feltus Lab](https://www.clemson.edu/science/departments/genetics-biochemistry/people/profiles/ffeltus), [Hasenauer Lab](https://www.mathematics-and-life-sciences.uni-bonn.de/en/group-members/jan-hasenauer), and [Robert C. Blake](https://bbs.llnl.gov/RobertBlake.html) from LLNL.

## The Acronym:
The acronym SPARCED is composed of following elements, based on the sub-models in the large-scale mechanistic model.

### S: SBML
### P: Proliferation
### A: Apoptosis
### R: Receptor Signaling
### C: Cell Cycle
### E: Expression
### D: DNA Damage

Owner

GitHub Events