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Oncology

2018

Genomics

Articles 1 - 2 of 2

Full-Text Articles in Life Sciences

A Tail Of Two Pancancer Projects: Somatic Variant Identification And Driver Gene Discovery Using Tcga, Matthew Hawkins Bailey Dec 2018

A Tail Of Two Pancancer Projects: Somatic Variant Identification And Driver Gene Discovery Using Tcga, Matthew Hawkins Bailey

Arts & Sciences Electronic Theses and Dissertations

The implementation of next-generation genomic sequencing has exploded over the past dozen years. Large consortia, such as The Cancer Genome Atlas (TCGA); the International Cancer Genetics Consortium (ICGC); and the Pediatric Cancer Genome Projects (PCGP), made great strides in democratizing big data for the scientific community. These data sets provide a rich resource to build tools for somatic variant discovery and exploratory analysis. Public repositories hold the answer to many novel biological and clinical revelations i.e., the discovery of complex indels, splice creating mutations, alternative super enhancer binding sites, machine learning models to predict mutation impact, and cancer subtype classification …


Discerning Drivers Of Cancer: Computational Approaches To Somatic Exome Sequencing Data, Runjun Kumar May 2018

Discerning Drivers Of Cancer: Computational Approaches To Somatic Exome Sequencing Data, Runjun Kumar

Arts & Sciences Electronic Theses and Dissertations

Paired tumor-normal sequencing of thousands of patient’s exomes has revealed millions of somatic mutations, but functional characterization and clinical decision making are stymied because biologically neutral ‘passenger’ mutations greatly outnumber pathogenic ‘driver’ mutations. Since most mutations will return negative results if tested, conventional resource-intensive experiments are reserved for mutations which are observed in multiple patients or rarer mutations found in well-established cancer genes. Most mutations are therefore never tested, diminishing the potential to discover new mechanisms of cancer development and treatment opportunities. Computational methods that reliably prioritize mutations for testing would greatly increase the translation of sequencing results to clinical …