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viSNE and Wanderlust, two algorithms for the visualization and analysis of high-dimensional single-cell data

El-ad David Amir

Title:
viSNE and Wanderlust, two algorithms for the visualization and analysis of high-dimensional single-cell data
Author(s):
Amir, El-ad David
Thesis Advisor(s):
Pe'er, Dana
Date:
Type:
Theses
Degree:
Ph.D., Columbia University
Department(s):
Biological Sciences
Persistent URL:
Abstract:
The immune system presents a unique opportunity for studying development in mammals. White blood cells undergo differentiation and proliferation, a never-ending process throughout the life of the organism. Hematopoiesis, the development of cells in the immune system, depends upon the interaction between many different cell types (some of which comprise less than a tenth of a percent of the population), transient regulatory decisions, genomic rearrangement events, cell proliferation, and death. To capture these events we employ mass cytometry, a novel technology that measures fifty proteins simultaneously in single cells. Mass cytometry results in large quantities of high-dimensional data which challenges existing computational techniques. To address these challenges, we developed two dimensionality reduction algorithms for analyzing mass cytometry and other single-cell data. The first, viSNE, transforms high-dimensional data into an intuitive two-dimensional map, making it accessible to visual exploration. The second algorithm, Wanderlust, receives as input a static snapshot (where cells occupy different stages of their development) and constructs their developmental ordering: the developmental trajectory. viSNE maps healthy bone marrow into a canonical shape that separates cell subtypes. In leukemia, however, the shape is malformed: the maps of cancer samples are distinct from the healthy map and from each other. The algorithm highlights structure in the heterogeneity of surface phenotype expression in cancer, traverses the progression from diagnosis to relapse, and identifies a rare leukemia population in minimal residual disease settings. Wanderlust was applied to healthy B lineage cells, where the trajectory follows known marker expression trends and genetic recombination events. Using the Wanderlust trajectory we identified CD24 as an early marker of B cell development. The trajectory captures the coordination between several regulatory mechanisms (surface marker expression, signaling, proliferation and apoptosis) during crucial development checkpoints. As new technologies raise the number of simultaneously measured parameters in each cell to the hundreds, viSNE and Wanderlust will become a mainstay in analyzing and interpreting such experiments.
Subject(s):
Immunology
Bioinformatics
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572
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Suggested Citation:
El-ad David Amir, , viSNE and Wanderlust, two algorithms for the visualization and analysis of high-dimensional single-cell data, Columbia University Academic Commons, .

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