University of Illinois Urbana-Champaign

Machine leanring algorithms for single-cell data analysis

Peng, Jianhao

Content Files
PENG-DISSERTATION-2022.pdf

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https://hdl.handle.net/2142/115567

Description

Title
Machine leanring algorithms for single-cell data analysis
Author(s)
Peng, Jianhao
Issue Date
2022-04-22
Director of Research (if dissertation) or Advisor (if thesis)
Milenkovic, Olgica
Doctoral Committee Chair(s)
Milenkovic, Olgica
Committee Member(s)
  • Ochoa, Idoia
  • Raginsky, Maxim
  • Shormonoy, Ilan
Department of Study
Electrical & Computer Eng
Discipline
Electrical & Computer Engr
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
  • single cell
  • online algorithm
  • network analysis
  • gene regulatory network
Abstract
In this thesis, we proposed various machine learning algorithms for analyzing different types of single cell sequencing data. Starting with the most common single cell RNA-seq data in Chapter 2, we proposed an online convex matrix factorization algorithm named online cvxMF that can efficiently learn representatives and interpretable lower-dimension basis vectors for each cell type. In Chapter 3, we introduced ChIA-Drop, a new type of network-structured data for chromatin interaction analysis, and extended our online cvxMF algorithm to a novel online convex network dictionary learning method that includes MCMC sampling and Gene Ontology enrichment analysis. The newly proposed method, online cvxNDL, is able to accurately reconstruct the original ChIA-Drop network and provide network dictionaries associated with biological functions. Lastly in Chapter 4, we proposed SimiC, a single cell gene regulatory network (GRN) inference algorithm that can jointly learn several GRNs from related cell phenotypes. Combined with regulon activity scores and regulatory dissimilarity scores for each of the driver genes across different phenotypes, SimiC is able to capture regulatory dynamics that are missed by previous methods.
Graduation Semester
2022-05
Type of Resource
Thesis
Handle URL
https://hdl.handle.net/2142/115567
Copyright and License Information
Copyright 2022 Jianhao Peng

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Graduate Dissertations and Theses at Illinois PRIMARY
Graduate Theses and Dissertations at Illinois