Jupyter notebook-based tools for building structured datasets from the Sequence Read Archive
This repository implements a pair of Jupyter notebook-based tools that utilize the MetaSRA for building structured datasets from the SRA in order to facilitate secondary analyses of the SRA’s human RNA-seq data:
- Case-Control Finder: Finds suitable case and control samples for a given disease or condition where the cases and controls are matched by tissue or cell type.
- Series Finder: Finds ordered sets of samples for the purpose of addressing biological questions pertaining to changes over a numerical property such as time.
For a more in depth description of these tools, please see our publication:
A few things to note:
- These notebooks currently utilize the MetaSRA version 1.6.
- This repository was copied and modified from the following repository: https://github.com/NCBI-Hackathons/RNA-Seq-in-the-Cloud/tree/master/Metadata. These tools were developed at an NCBI computational biology codeathon in March 2019 held in Chapel Hill, North Carolina.
Running the notebooks on Google Colab
The notebooks can be executed in the cloud via Google Colab:
Running the notebooks locally
Setup
The dependencies for these notebooks are described in requirements.txt. To install these dependencies, please run
pip install -r requirements.txt
Furthermore, before running the notebook, you must unpack the static metadata files from data.tar.gz. To do so, run the following command:
tar -zcf data.tar.gz
Running the notebooks
To run the Case-Control Finder, run:
jupyter notebook case_control_finder.ipynb
To run the Series Finder, run:
jupyter notebook series_finder.ipynb
Contributors
- Matthew Bernstein
- Emily Clough
- Ariella Gladstein
- Khun Zaw Latt
- Ben Busby
- Allissa Dillman