Title :
Automated image analysis and inference of gene function from high - Content screens
Author :
Raja, Priyanka J. ; Jacob, Jeevamma ; Byung-Jun Yoon ; Bartholomeusz, Geofferey ; Rao, Akhila
Author_Institution :
Dept. of Bioinf. & Comput. Biol., Univ. of Texas MD Anderson Cancer Center, Houston, TX, USA
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.
Keywords :
cancer; feature extraction; medical image processing; tumours; automated image analysis; bag of word based clustering approach; gene function; high content RNAi screen; large scale 3D RNAi screens; morphological feature extraction; novel automated pipeline; phenotypic clusters; tumor biology; tumor cell morphology; viable cancer therapeutics; Clustering algorithms; Earth; Feature extraction; Histograms; Measurement; Morphology; Tumors; affinity propagation clustering; earth movers distance; high content screening; image analysis; image processing; machine learning; textural features;
Conference_Titel :
Signal Processing Conference (EUSIPCO), 2013 Proceedings of the 21st European
Conference_Location :
Marrakech
