Cell fate engineering tools for iPSC disease modeling

Emily K.W. Lo, Patrick Cahan

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

The field of cell fate engineering is contingent on tools that can quantitatively assess the efficacy of cell fate engineering protocols and experiments. CellNet is such a cell fate assessment tool that utilizes network biology to both evaluate and suggest candidate transcriptional regulatory modifications to improve the similarity of an engineered population to its corresponding in vivo target population. CellNet takes in expression profiles in the form of RNA-sequencing data and generates several metrics of cell identity and protocol efficacy. In this chapter, we demonstrate how to (1) preprocess raw RNA-sequencing data to generate an expression matrix, (2) train CellNet using preprocessed expression matrices, and (3) apply CellNet to a query study and interpret its results. We demonstrate the utility of CellNet for analysis of iPSC disease modeling studies, which we evaluate through the lens of cell fate engineering.

Original languageEnglish (US)
Title of host publicationMethods in Molecular Biology
PublisherHumana Press Inc.
Pages427-454
Number of pages28
DOIs
StatePublished - 2019

Publication series

NameMethods in Molecular Biology
Volume1975
ISSN (Print)1064-3745
ISSN (Electronic)1940-6029

Keywords

  • Cell fate engineering
  • Computational biology
  • Disease modeling
  • Gene expression profiling
  • Gene regulatory networks
  • Stem cells

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics

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