Meet the team

Meet our CI Facilitators

2023 Cohort

Facilitator: Rebecca Belshe

Project title: Enabling Multiple Allele Effects Faculty

Researcher: Michael Lynch

Project description: This project pairs CI facilitator Rebecca Belshe with Dr. Michael Lynch of the ASU Center for Mechanisms of Evolution. A computational model of phylogenetic lineages incorporating effects such as selection and drift incurs a large memory footprint with multiple mutations. Several multidimensional arrays have been employed to characterize the dynamics, including interference between these mutations, within the population. These arrays are very sparse, and their scale limits the number of mutations that can be included in the model. This project aims to explore and implement a new memory model, benchmark its impact on performance, deliver a new working code, and present a summary report. The project is scheduled to conclude in January 2024.

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Facilitator: Susan Massey

Project title: TCGA Sex Chromosome Status Pipeline Faculty

Researcher: Melissa Wilson

Project description: This project pairs CI facilitator Susan Massey with Dr. Melissa Wilson of the ASU School of Life Sciences. The goal of this project is to develop a workflow for the analysis of sex chromosomes in cancer genomics. Sex chromosomes have long been overlooked in cancer research. As such, there is a need to assess the status of sex chromosomes in the existing sequenced samples of the Cancer Genome Atlas (TCGA) and evaluate their impact on patient outcomes. This project supports the effort to study this through the development of a computational workflow to import TCGA genomic data and determine the presence of a Y chromosome and/or the status of XIST, a marker of X chromosome inactivation, in the samples. The resulting inferred sex chromosome complement will be compared to subjects’ clinically recorded sex, and will then be used in further analyses of outcome (survival analysis) and disease severity (cancer stage). After completion, this reproducible workflow can be applied to additional cancer types. The project is scheduled to conclude in February 2024 with the delivery of a data table, an R script, and a summary report.