Reconstructing Sample-Specific Networks using LIONESS

bioRxiv (Cold Spring Harbor Laboratory)

Abstract

Abstract We recently developed LIONESS, a method to estimate sample-specific networks based on the output of an aggregate network reconstruction approach. In this manuscript, we describe how to apply LIONESS to different network reconstruction algorithms and data types. We highlight how decisions related to data preprocessing may affect the output networks, discuss expected outcomes, and give examples of how to analyze and compare single sample networks.

Authors 2

1. Marieke L. Kuijjer corresponding Aachen Department of Pathology, Leiden University Medical Center

   University of Oslo · Leiden University Medical Center

   Affiliation as printed

   Center for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo, 0318 Oslo, Norway

   Department of Pathology, Leiden University Medical Center, 2300RC Leiden, the Netherlands

   Center for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo

   Department of Pathology, Leiden University Medical Center

2. Kimberly Glass

   Brigham and Women's Hospital · Harvard University

   Affiliation as printed

   Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA 02115, USA

   Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA

   Department of Medicine, Harvard Medical School, Boston, MA 02115, USA

   Channing Division of Network Medicine, Brigham and Women’s Hospital

   Department of Biostatistics, Harvard School of Public Health

   Department of Medicine, Harvard Medical School