Integrating DNA methylation and gene expression data in a single gene network using the iNETgrate package

Sogand Sajedi, Ghazal Ebrahimi, Raheleh Roudi, Isha Mehta, Amirreza Heshmat, Hanie Samimi, Shiva Kazempour, Aamir Zainulabadeen, Thomas Roderick Docking, Sukeshi Patel Arora, Francisco Cigarroa, Sudha Seshadri, Aly Karsan, Habil Zare

Research output: Contribution to journalArticlepeer-review

Abstract

Analyzing different omics data types independently is often too restrictive to allow for detection of subtle, but consistent, variations that are coherently supported based upon different assays. Integrating multi-omics data in one model can increase statistical power. However, designing such a model is challenging because different omics are measured at different levels. We developed the iNETgrate package (https://bioconductor.org/packages/iNETgrate/) that efficiently integrates transcriptome and DNA methylation data in a single gene network. Applying iNETgrate on five independent datasets improved prognostication compared to common clinical gold standards and a patient similarity network approach.

Original languageEnglish (US)
Article number21721
JournalScientific reports
Volume13
Issue number1
DOIs
StatePublished - Dec 2023

ASJC Scopus subject areas

  • General

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