Skip to content

A suite of scientific workflows to assess metrics to compare efficacy of protein-based tumor deconvolution algorithms.

License

Notifications You must be signed in to change notification settings

PNNL-CompBio/decomprolute

Repository files navigation

Decomprolute: Benchmarking study of proteomic based tumor deconvolution

The goal of this package is to provide a framework for the benchmarking of tumor deconvolution algorithms specifically on proteomics data. To run the platform, please see our primary documentation site.

Here we describe how to contribute to the project. We employ a modular, containerized, framework written in the Common Workflow Language to enable plug-n-play assessment of novel algorithms as described in the image below.

image

Status of docker builds:

Status Description
Protein docker builds Collects CPTAC protein data
mRNA docker builds Collects CPTAC mRNA data
Algorithm docker builds Builds deconvolution docker images
Figures and correlation docker builds Builds metrics and figure docker images
Immune subtypes docker builds Builds immune subtypes and distance metric docker images

How to contribute

As a benchmarking platform, we constructed an architecture that enables others to contribute and add their own customization. While our documentation site has information on how to run the platform, this page focuses on how to contribute.

Adding a new algorithm

Once you have written an algorithm, we require first a script to run the algorithm, and then integration into our larger script.

To add a tumor deconvolution algorithm this platform requires two inputs:

  1. An expression matrix
  2. A cell type matrix

As such we recommend building a Docker container that runs your algorithm together with a Common Workflow Language script to run the algorithm with the two inputs (labeled expression and signature. The expected output is a matrix called deconvoluted.

Once you have a script that can run, you can modify the run-deconv.cwl script in the ./tumorDeconvAlgs directory. This script takes the same parameters as the script described above but also an additional parameter called alg.

Once this is complete, you should be able to run a test command such as

cwltool https://raw.githubusercontent.com/PNNL-CompBio/decomprolute/main/metrics/prot-deconv.cwl --cancer hnscc --protAlg [yourAlgNameHere] --sampleType tumor --signature LM7c

Once this test script can run, you can create a pull request from your fork.

Adding a new cell type matrix

It is important to test new signature matrices as they evolve, and therefore we created a separate module to enable the creation of custom cell-type matrices.

The easiest way to add a custom signature matrix is to copy a weighted matrix into the ./signature_matrices directory. The rows of the matrix represent gene names (the first column should be an HGNC gene name) and the columns represent cell types. Once the docker image rebuilds with this file in the directory, it can be called by the cwl script.

Updating documentation

We also try to keep our documentation site up to date. If you have any updates to this, please create a pull request with updates to the docs/index.md page.

Software requirements

To implement your algorithm in this framework, you will need a CWL engine and Docker installed.

About

A suite of scientific workflows to assess metrics to compare efficacy of protein-based tumor deconvolution algorithms.

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Contributors 4

  •  
  •  
  •  
  •