Automated image analysis and inference of gene function from high - Content screens

Priyanka J. Raja, Justin Jacob, Byung Jun Yoon, Geofferey Bartholomeusz, Arvind Rao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The study of tumor biology and heterogeneity is of high importance for identifying viable cancer therapeutics. A high content RNAi screen is carried out to identify genes that induce varied tumor morphologies. We present a novel automated pipeline to identify and interpret gene function by extracting morphological features of tumor cell aggregates, in large scale 3D RNAi screens. We use a 'bag of words' based clustering approach to distinguish multiple phenotypes. Functional analysis of genes underlying the phenotypic clusters reveals the role of growth and invasion modulators in shaping tumor cell morphology and heterogeneity.

Original languageEnglish (US)
Title of host publication2013 Proceedings of the 21st European Signal Processing Conference, EUSIPCO 2013
PublisherEuropean Signal Processing Conference, EUSIPCO
ISBN (Print)9780992862602
StatePublished - 2013
Event2013 21st European Signal Processing Conference, EUSIPCO 2013 - Marrakech, Morocco
Duration: Sep 9 2013Sep 13 2013

Publication series

NameEuropean Signal Processing Conference
ISSN (Print)2219-5491

Other

Other2013 21st European Signal Processing Conference, EUSIPCO 2013
Country/TerritoryMorocco
CityMarrakech
Period9/9/139/13/13

Keywords

  • affinity propagation clustering
  • earth movers distance
  • high content screening
  • image analysis
  • image processing
  • machine learning
  • textural features

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

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