henhaobio
Sign in

bioRxivSystems BiologyPreprint

PyIOmica: Longitudinal Omics Analysis and Classification

Sergii DomanskyiiD, Carlo PiermarocchiiD, George I. MiasiD

PDFDOI

Abstract

SummaryPyIOmica is an open-source Python package focusing on integrating longitudinal multiple omics datasets, characterizing, and classifying temporal trends. The package includes multiple bioinformatics tools including data normalization, annotation, classification, visualization, and enrichment analysis for gene ontology terms and pathways. Additionally, the package includes an implementation of visibility graphs to visualize time series as networks.\n\nAvailability and implementationPyIOmica is implemented as a Python package (pyiomica), available for download and installation through the Python Package Index (PyPI) (https://pypi.python.org/pypi/pyiomica), and can be deployed using the Python import function following installation. PyIOmica has been tested on Mac OS X, Unix/Linux and Microsoft Windows. The application is distributed under an MIT license. Source code for each release is also available for download on Zenodo (https://doi.org/10.5281/zenodo.3342612).\n\nContactgmias@msu.edu

Citations
1

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISMias '16Meng '22Pan '19Gao '21Harbig '22Perrin '26
65% semantic matchBioinformatics
George I. Mias, Tahir Yusufaly, Raeuf Roushangar+3 more·Scientific Reports·Nov 24, 2016· 27 citations