Kuijjer Lab

New BioRχiv pre-print

November 01, 2022

We have posted a new version of our previous BioRχiv pre-print on large-scale network analysis by Tatiana. We modeled networks for individual soft-tissue sarcoma patients and identified large regulatory heterogeneity in leiomyosarcomas. To characterize this regulatory heterogeneity, Tatiana developed a new algorithm, called PORCUPINE. PORCUPINE is a permutation-based approach that uses Principal Components Analysis to identifies pathways that significantly contribute to regulatory heterogeneity in a patient population. We applied the method to an independent leiomyosarcoma dataset and used leiomyosarcoma cell lines to validate identified pathways and genes that drive patient heterogeneity. More information on the pre-print can be found here.

Schematic overview of the analysis presented in our BioRχiv pre-print. We modeled individual patient gene regulatory networks for leiomyosarcoma patients from two datasets (TCGA and DKFZ) with PANDA and LIONESS, integrating information on protein-protein interactions (PPI) between transcription factors (TF), prior information on TF-DNA motif binding, and gene expression data. We then developed and applied a new computational comparative network analysis tool (PORCUPINE) to identify significant pathways that capture heterogeneity in gene regulation across these datasets.