adenine is a machine learning framework designed for biological data exploration and visualization. Its goal is to help bioinformaticians achieving a first and quick overview of the main structures underlying their data. This software tool encompasses state-of-the-art techniques for missing values imputing, data preprocessing, dimensionality reduction and clustering. adenine has a scalable architecture which seamlessly work on single workstations as well as on high-performance computing facilities. adenine is capable of generating publication-ready plots along with quantitative descriptions of the results. In this paper we provide an example of exploratory analysis on a publicly available gene expression data set of colorectal cancer samples. The software and its documentation are available at https://github.com/slipguru/adenine under FreeBSD license.
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Titolo: | Adenine: A HPC-oriented tool for biological data exploration |
Autori: | |
Data di pubblicazione: | 2019 |
Serie: | |
Handle: | http://hdl.handle.net/11567/942953 |
ISBN: | 9783030141592 |
Appare nelle tipologie: | 02.01 - Contributo in volume (Capitolo o saggio) |