The Community for Technology Leaders
RSS Icon
Subscribe
Issue No.04 - October-December (2009 vol.6)
pp: 652-666
Hiroaki Uehara , Keio University, Yokohama
Masakazu Jimbo , Nagoya University, Nagoya
ABSTRACT
The study of gene functions requires high-quality DNA libraries. However, a large number of tests and screenings are necessary for compiling such libraries. We describe an algorithm for extracting as much information as possible from pooling experiments for library screening. Collections of clones are called pools, and a pooling experiment is a group test for detecting all positive clones. The probability of positiveness for each clone is estimated according to the outcomes of the pooling experiments. Clones with high chance of positiveness are subjected to confirmatory testing. In this paper, we introduce a new positive clone detecting algorithm, called the Bayesian network pool result decoder (BNPD). The performance of BNPD is compared, by simulation, with that of the Markov chain pool result decoder (MCPD) proposed by Knill et al. in 1996. Moreover, the combinatorial properties of pooling designs suitable for the proposed algorithm are discussed in conjunction with combinatorial designs and d\hbox{-}{\rm disjunct} matrices. We also show the advantage of utilizing packing designs or BIB designs for the BNPD algorithm.
INDEX TERMS
DNA library screening, high-throughput screening, pooling experiment, two stage test, group testing, Bayesian network, sum-product algorithm, LDPC.
CITATION
Hiroaki Uehara, Masakazu Jimbo, "A Positive Detecting Code and Its Decoding Algorithm for DNA Library Screening", IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol.6, no. 4, pp. 652-666, October-December 2009, doi:10.1109/TCBB.2007.70266
REFERENCES
[1] E. Barillot, B. Lacroix, and D. Cohen, “Theoretical Analysis of Library Screening Using an $N\hbox{-}{\rm Dimensional}$ Pooling Strategy,” Nucleic Acids Research, vol. 19, no. 22, pp. 6241-6247, 1991.
[2] T. Berger, J.W. Mandell, and P. Subrahmanya, “Maximally Efficient Two-Stage Screening,” Biometrics, vol. 56, no. 3, pp.833-840, 2000.
[3] W.J. Bruno, E. Knill, D.J. Balding, D.C. Bruce, N.A. Doggett, W.W. Sawhill, R.L. Stallings, C.C. Whittaker, and D.C. Torney, “Efficient Pooling Designs for Library Screening,” Genomics, vol. 26, no. 1, pp. 21-30, 1995.
[4] D.Z. Du and F.K. Hwang, Combinatorial Group Testing and Its Application. World Scientific, 2000.
[5] A.G. D'yachkov, F.K. Hwang, A.J. Macula, P.A. Vilenkin, and C. Weng, “A Construction of Pooling Designs with Some Happy Surprises,” J. Computational Biology, vol. 12, no. 8, pp. 1129-1136, 2005.
[6] R.G. Gallager, “Low-Density Parity-Check Codes,” IRE Trans. Information Theory, vol. 8, pp. 21-28, 1962.
[7] E. Knill, A. Schliep, and D.C. Torney, “Interpretation of Pooling Experiments Using the Markov Chain Monte Carlo Method,” J.Computational Biology, vol. 3, no. 3, pp. 395-406, 1996.
[8] D.J.C. MacKay and R.M. Neal, “Near Shannon Limit Performance of Low Density Parity Check Codes,” IEE Electronics Letters, vol. 32, no. 18, pp. 1645-1655, 1996.
[9] A.J. Macula, “Probabilistic Nonadaptive Group Testing in the Presence of Errors and DNA Library Screening,” Ann. Combinatorics, vol. 3, no. 1, pp. 61-69, 1999.
[10] M. Mézard and C. Toninelli, “Group Testing with Random Pools: Optimal Two-Stage Algorithms,” arXiv:0706.3104, 2007.
[11] W.H. Mills and R.C. Mullin, “Coverings and Packings,” Contemporary Design Theory: A Collection of Surveys, J.H. Dinitz and D.R. Stinson, eds., pp. 317-399, John Wiley & Sons, 1992.
[12] H.Q. Ngo and D.Z. Du, “A Survey on Combinatorial Group Testing Algorithms with Applications to DNA Library Screening,” Discrete Math. Problems with Medical Applications, DIMACS Ser. Discrete Math. and Theoretical Computer Science, vol. 55, pp. 171-182, 2000.
[13] J. Pearl, Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann, 1997.
[14] P. Sham, J.S. Bader, I. Craig, M. O'Donovan, and M. Owen, “DNA Pooling: A Tool for Large-Scale Association Studies,” Nature Rev. Genetics, vol. 3, no. 11, pp. 862-871, Nov. 2002, .
[15] N. Thierry-Mieg, “A New Pooling Strategy for High-Throughput Screening: The Shifted Transversal Design,” BMC Bioinformatics, vol. 7, no. 28, 2006.
[16] W. Wu, Y. Li, C.H. Huang, and D.Z. Du, “Molecular Biology and Pooling Design,” Proc. Workshop Data Mining in Biomedicine (DMB '04), Feb. 2004.
[17] http://www.nature.com/reviews/geneticshttp:/ /jim.math.cm.is.nagoya-u.ac.jp/~uehara bnpd/, 2008.
[18] http:/algorithmics.molgen.mpg.de/, 2008.
19 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool