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Student Brown Bag Discussion: Amin Emad Semi-Quantitative Group Testing: A Novel Approach to High Throughput Genotyping

Amin Emad
Graduate Student
Electrical and Computer Engineering
University of Illinois

Related Resources:

Semi-Quantitative Group Testing: A Novel Approach to High Throughput Genotyping

Keywords:

genotyping, DNA, Virtual Brown Bag Research Series,

Center for Science of Information presents a Student Brown Bag Presentation by 

Amin Emad, PhD student, University of Illinois

VIEW THE RECORDED PRESENTATION

Abstract:

"Genotyping is the process of identifying variations in the genetic makeup (genotype) of individuals of a large population. One of its most important applications is to determine the gene alleles that cause genetic diseases in humans. Until very recently, the DNA sequencers used to find these “positive” alleles only allowed serial processing of a specific region of the genome. Recently, new developments of the “next-generation sequencing technologies” allow for parallel processing of these regions; however, in order to make these technologies (cost) efficient, one needs to take advantage of ideas from compressed sensing and group testing.

Group testing is a method of finding “positives” in large populations by testing subsets of the population. In this work, we address the issues in applying group testing to the new genotyping paradigm and introduce a new paradigm dubbed “semi-quantitative group testing (SQGT)” to address some of these issues. SQGT is a non-binary pooling scheme that may be viewed as a combination of an adder model followed by aquantizer. For the new testing scheme we define the capacity and evaluate the capacity for some special choices of parameters using information theoretic methods. We also define a new class of disjunct codes suitable for SQGT, termed SQ-disjunct codes. We also provide both explicit and probabilistic code construction methods for SQGT with simple decoding algorithms."

Related References:

1. W. Kautz and R. Singleton, “Nonrandom Binary Superimposed Codes,” IEEE Trans. Inf. Theory, vol. 10, no. 4, pp. 363-377, Oct. 1964.
    
2. Wei Dai, Mona A. Sheikh, Olgica Milenkovic, Richard G. Baraniuk, "Compressive Sensing DNA Microarrays," EURASIP J. Bioinformatics and Systems Biology, 2009.
    
3. Y. Erlich, K. Chang, A. Gordon, R. Ronen, O. Navon, M. Rooks and G. J. Hannon, "DNA Sudoku - harnessing high-throughput sequencing for multiplexed specimen analysis," Genome Research, 2009.

Event Link: https://gomeet.itap.purdue.edu/p69427118/