Shayna Mallett

Computer science

Hometown: Los Alamos, New Mexico, United States

Graduation date: Spring 2022

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FURI | Spring 2022

Graph-Guided Assembly and Typing of the HLA Alleles from RNA-seq Data

Human Leukocyte Antigens (HLA) are encoded by a polymorphic set of genes where even a single base change can impact the function of the body’s immune response to foreign antigens (Gao, 2001). Although many methods exist to type these alleles using whole-genome sequencing, few can use the more popular RNA sequencing with its inconsistency in coverage, and none of these allow for novel allele discovery. Using partially ordered graphs to project sequenced data onto the known alleles will allow for accurate and efficient typing of HLA with flexibility for discovering new alleles and tolerance for poor sequence quality.

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Additional projects from this student

Accurately and efficiently typing human leukocyte antigen alleles is essential to successful organ transplants and has potential for precision medicine.

Mentor:

  • FURI
  • Fall 2021

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