Protein identification with Comet, PeptideProphet and ProteinProphet using BioDocker containers

By +Yasset Perez-Riverol  and +Felipe Leprevost:

Proteomics data analysis is dominated by database-based search engines strategies. Perhaps the most common protocol today is to retrieve raw data from a mass spectrometry, convert the raw data from binary format to a text-based format and then process it using a database search algorithm. The resulting data need to be statistically filtered in order to converge to a final list of identified peptides and proteins.

Amount Search Engines, Comet (the youngest son of SEQUEST) is one of the most popular nowadays. Today we are going to show how to run a simple analysis protocol using the Comet database search engine followed by statistical analysis using PeptideProphet and ProteinProphet, two of the most known and robust processing algorithms for proteomics data.

This pipeline is available in TPP, however several users prefer to use the individual components rather than Trans-proteomics Pipeline.  The big differential here is how we are going to do it. Instead of going through the step-by-step in how to install and configure Comet and TPP, we are going to run the pipeline using Docker containers from the BioDocker project (you can get more information on the project here).

A Trans-Proteomic Pipeline (TPP) Docker container

By +Felipe Leprevost & +Yasset Perez-Riverol

In my initial post in this blog, I will teach you how to use a Docker container with the Trans-Proteomic Pipeline software installation.

Docker is a great new technology that allows us to create GNU/Linux containers with specific software inside. All kinds of software can be "containerized", including ones that rely on graphical user interfaces.

The whole idea of using a Docker container is built on having a software that is isolated from the host OS and can interact with the outside world. GNU/Linux containers, like Docker, are very useful even in the scientific world where bioinformatics applications are used every day.

Using Docker with bioinformatics software helps to solve some issues we face, like reproducibility, for example. We wrote about this last year [1] . You can also check for more containers with bioinformatics applications in the BioDocker webpage.

Here I am going to describe to you how to install and use one of the most powerful software for proteomics data analysis, the Trans-Proteomics Pipeline (TPP).

Unfortunately, if you are a GNU/Linux user (like me) and your job involve MS/MS data analysis (also, like me), you will probably have some harsh time trying to install TPP. Almost all the tutorials available on the Web focus on the Windows users, so novice bioinformaticians or those that are not too versatile with GNU/Linux can have some hard times.

With a Docker TPP container you can just download it and use it on the command line, the container it self behaves like an executable, so image the possibilities.

Lets begin preparing your environment for Docker. The first thing you have to do is to install some libraries that are essential for the Docker daemon to run properly. If you are running an Ubuntu OS, you can skip this step. If you are on a different OS, like Linux Mint for example you need to follow these steps.

Installing standalone SpectraST in linux

Some tips to install SpectraST in linux in standalone:

1. -  Download TTP latest version.
2. -  go to SpectraST folder and run make:
     
    cd TPP-x.x.x/trans_proteomic_pipeline/src/Search/SpectraST
    make -f Makefile_STANDALONE_LINUX