Sean Pascoe

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Originally from Tucson, AZ, Sean is a rising senior at Northwestern University studying biology with minors in Data Science and French. At Northwestern, Sean works in the lab of Dr. Thomas Hope, where he has highlighted trends in PET/CT and vaccine trial data to better understand the dynamics of HIV infection. He is passionate about science education, as well as finding ways to integrate computational biology work with the discovery of niche coffee shops in Chicago. At UCLA, Sean is working in the Meyer lab to decipher complex immune cell relationships within and between patients with systemic lupus erythematosus (SLE). Single cell RNA sequencing (scRNA-seq) is used to profile heterogeneity in biological systems, but current analysis strategies lack the ability to robustly differentiate patient-to-patient variation when comparing samples across many different individuals. To profile multi-experiment scRNA-seq data, the Meyer lab has adapted PARAFAC2, a multidimensional variance decomposition method, to first align data between experiments and subsequently perform dimensionality reduction. PARAFAC2 enables a 3-dimensional approach to linear decompositions of scRNA-seq data, and is thus better able to model natural variation. This summer, Sean is applying this method to 1.2 million cells derived from 260 patients, with the goal of using PARAFAC2 to strengthen understanding of the cell-level changes that contribute to the SLE disease state. Sean would like to thank Andrew Ramirez, Dr. Meyer, and the rest of the Meyer lab for their invaluable support throughout the summer, as well as the Amgen Scholars program at UCLA for this opportunity.

Originally from Tucson, AZ, Sean is a rising senior at Northwestern University studying biology with minors in Data Science and French. At Northwestern, Sean works in the lab of Dr. Thomas Hope, where he has highlighted trends in PET/CT and vaccine trial data to better understand the dynamics of HIV infection. He is passionate about science education, as well as finding ways to integrate computational biology work with the discovery of niche coffee shops in Chicago.

At UCLA, Sean is working in the Meyer lab to decipher complex immune cell relationships within and between patients with systemic lupus erythematosus (SLE). Single cell RNA sequencing (scRNA-seq) is used to profile heterogeneity in biological systems, but current analysis strategies lack the ability to robustly differentiate patient-to-patient variation when comparing samples across many different individuals. To profile multi-experiment scRNA-seq data, the Meyer lab has adapted PARAFAC2, a multidimensional variance decomposition method, to first align data between experiments and subsequently perform dimensionality reduction. PARAFAC2 enables a 3-dimensional approach to linear decompositions of scRNA-seq data, and is thus better able to model natural variation. This summer, Sean is applying this method to 1.2 million cells derived from 260 patients, with the goal of using PARAFAC2 to strengthen understanding of the cell-level changes that contribute to the SLE disease state.

Sean would like to thank Andrew Ramirez, Dr. Meyer, and the rest of the Meyer lab for their invaluable support throughout the summer, as well as the Amgen Scholars program at UCLA for this opportunity.