Talk title:
Using ENCODE Data for Cancer Genomics
Abstract:
My talk will focus on leveraging thousands of functional genomics
datasets to annotate the cancer genome and perform data mining to
discover cancer-associated regulators and variations.
First, I will introduce our computational efforts to perform
large-scale integration to accurately define distal and proximal
regulatory elements (MatchedFilter) and then show how our extended
gene annotation allows us to place oncogenic transformations in the
context of a broad cell space; here, many normal-to-tumor transitions
move towards a stem-like state, while oncogene knockdowns show an
opposing trend.
Second, I will look at our comprehensive regulatory networks of
transcription factors and RNA-binding proteins (TFs and RBPs). I will
showcase their value by highlighting how SUB1, a previously
uncharacterized RBP, drives aberrant tumor expression and amplifies
the effect of the well-known oncogenic TF MYC.
Third, I will introduce a workflow to prioritize key elements and
variants. I will showcase the application of this prioritization to
somatic burdening, cancer differential expression, and GWAS (LARVA,
MOAT & uORF tools). Targeted validations of the prioritized
regulators, elements, and variants demonstrate the value of our
annotation resource.
URL:
http://encodec.encodeproject.org
http://radar.gersteinlab.org
http://MatchedFilter.gersteinlab.org
Venue:
ENCODE 2020 Users meeting
i0encusr
Tuesday, September 22, 2020
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