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System for turnkey analysis of semi-automated genome annotations

Project description


What is segzoo?

Segzoo is a tool that allows to run various genomic analysis on a segmentation obtained by segway. The results of each analysis are made available as well as a summarizing visualization of the results. The requirements for this tool include segtools, bedtools and python packages, but all of them are dependencies that will be treated during installation.

How to install

Segzoo is a python 3 tool, so if you have python 2 installed it is highly recommended for you to install segzoo in a separate python 3 environment. To create such an environment run conda create -n python3_env python==3.6 where you can change the name of the environment, python3_env. Accept all the installation steps.

Next, you need to activate this environment. Run source activate python3_env specifying the name of the environment you chose before. Now that you already are in it, you can install segzoo. You can do that by running pip install segzoo, which will require you to have bedtools already installed, as it's only in anaconda. Another option is to install it using conda install segzoo -c bioconda which will take care of all the dependencies (WIP).

After accepting all installations, segzoo will be good to go!

How to use

To access the help to know how to run segzoo you can run segzoo -h or segzoo --help. Here's a look at the most important parameters:

  • --parameters to specify a params.params file resulting from segway's training to obtain GMTK parameters in the final visualization.
  • --prefix to specify where you want all needed data (like genome assembly) to be downloaded. The default is in your current environment share directory.
  • -o or --outdir to specify the folder where all the results and the final visualization will be created

After running the command segzoo by specifying the segmentation file and all the optional arguments that you want, the execution of the pipeline will begin. All necessary data will be downloaded, tools will run the different analysis and the final visualization will be created. This execution may take some time.


After the execution has finished, the new directory will be created (outdir is the default name). In the data folder you will be able to find the results for all the tools' analysis. In results you will find the tables of processed results used in the visualization. In logs some relevant information about the run. Finally, the visualization will be in the plots directory. It will look something like this:


Y-axis are the labels of the segmentation for all the plots. As a note: the aggregation results displayed are the percentage of aggregations in one component in comparison for all the gene biotype, so notice that each row adds up 100.

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