학술논문

PyBDA: a command line tool for automated analysis of big biological data sets
Document Type
Original Paper
Source
BMC Bioinformatics. 20(1)
Subject
Big data
Data analysis
Command line
Pipeline
Computing cluster
Grid engine
Machine learning
Language
English
ISSN
1471-2105
Abstract
Background: Analysing large and high-dimensional biological data sets poses significant computational difficulties for bioinformaticians due to lack of accessible tools that scale to hundreds of millions of data points.Results: We developed a novel machine learning command line tool called PyBDA for automated, distributed analysis of big biological data sets. By using Apache Spark in the backend, PyBDA scales to data sets beyond the size of current applications. It uses Snakemake in order to automatically schedule jobs to a high-performance computing cluster. We demonstrate the utility of the software by analyzing image-based RNA interference data of 150 million single cells.Conclusion: PyBDA allows automated, easy-to-use data analysis using common statistical methods and machine learning algorithms. It can be used with simple command line calls entirely making it accessible to a broad user base. PyBDA is available at https://pybda.rtfd.io.