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MOMIC: A multi-omics pipeline for data analysis, integration and interpretation

Authors :
Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos
Universidad de Sevilla. TIC-254: Data Science and Big Data Lab
Universidad de Sevilla. TIC134: Sistemas Informáticos
Ministerio de Economía y Competitividad (MINECO). España
Junta de Andalucía
Ministerio de Ciencia e Innovación (MICIN). España
Madrid Márquez, Laura
Rubio Escudero, Cristina
Pontes Balanza, Beatriz
González Pérez, Antonio
Riquelme Santos, José Cristóbal
Sáez, María E.
Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos
Universidad de Sevilla. TIC-254: Data Science and Big Data Lab
Universidad de Sevilla. TIC134: Sistemas Informáticos
Ministerio de Economía y Competitividad (MINECO). España
Junta de Andalucía
Ministerio de Ciencia e Innovación (MICIN). España
Madrid Márquez, Laura
Rubio Escudero, Cristina
Pontes Balanza, Beatriz
González Pérez, Antonio
Riquelme Santos, José Cristóbal
Sáez, María E.
Publication Year :
2022

Abstract

Background and Objectives: The burst of high-throughput omics technologies has given rise to a new era in systems biology, offering an unprecedented scenario for deriving meaningful biological knowledge through the integration of different layers of information. Methods: We have developed a new software tool, MOMIC, that guides the user through the application of different analysis on a wide range of omic data, from the independent single-omics analysis to the combination of heterogeneous data at different molecular levels. Results: The proposed pipeline is developed as a collection of Jupyter notebooks, easily editable, reproducible and well documented. It can be modified to accommodate new analysis workflows and data types. It is accessible via momic.us.es, and as a docker project available at github that can be locally installed. Conclusions: MOMIC offers a complete analysis environment for analysing and integrating multi-omics data in a single, easy-to-use platform.

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1367041718
Document Type :
Electronic Resource