Study

Identification of cis-regulatory mutations generating de novo edges in personalized cancer gene regulatory networks

Study ID Alternative Stable ID Type
EGAS00001002571 Other

Study Description

The identification of functional non-coding mutations is a key challenge in the field of genomics. Here we introduce μ-cisTarget to filter, annotate and prioritize cis-regulatory mutations based on their putative effect on the underlying ‘personal’ gene regulatory network. We validated μ-cisTarget by re-analyzing the TAL1 and LMO1 enhancer mutations in T-ALL, and the TERT promoter mutation in melanoma. Next, we re-sequenced the full genome of ten cancer cell lines and used matched transcriptome data and motif discovery to identify master regulators with de novo binding sites that result in the up-regulation of nearby oncogenic drivers.

Study Datasets 1 dataset.

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Dataset ID Description Technology Samples
EGAD00001003824
Whole genome sequencing data on 10 human cancer cell lines
Complete Genomics,Illumina Genome Analyzer IIx 14

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