## An Algorithm for Clustering cDNAs for Gene Expression Analysis (1999)

Venue: | In RECOMB99: Proceedings of the Third Annual International Conference on Computational Molecular Biology |

Citations: | 46 - 4 self |

### BibTeX

@INPROCEEDINGS{Hartuv99analgorithm,

author = {Erez Hartuv and Armin Schmitt and Jörg Lange and Sebastian Meier-Ewert and Hans Lehrach and Ron Shamir},

title = {An Algorithm for Clustering cDNAs for Gene Expression Analysis},

booktitle = {In RECOMB99: Proceedings of the Third Annual International Conference on Computational Molecular Biology},

year = {1999},

pages = {188--197},

publisher = {ACM Press}

}

### Years of Citing Articles

### OpenURL

### Abstract

We have developed a novel algorithm for cluster analysis that is based on graph theoretic techniques. A similarity graph is defined and clusters in that graph correspond to highly connected subgraphs. A polynomial algorithm to compute them efficiently is presented. Our algorithm produces a clustering with some provably good properties. The application that motivated this study was gene expression analysis, where a collection of cDNAs must be clustered based on their oligonucleotide fingerprints. The algorithm has been tested intensively on simulated libraries and was shown to outperform extant methods. It demonstrated robustness to high noise levels. In a blind test on real cDNA fingerprint data the algorithm obtained very good results. Utilizing the results of the algorithm would have saved over 70% of the cDNA sequencing cost on that data set. 1 Introduction Cluster analysis seeks grouping of data elements into subsets, so that elements in the same subset are in some sense more cl...

### Citations

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Citation Context ...sentation of low-abundance genes must be 100,000 or more. Sequencing all 100,000 cDNAs in a sample is slow, wasteful and prohibitively expensive. An alternative method was proposed about a decade ago =-=[14, 3, 31, 4, 28, 22, 24]-=-. It is based on spotting the cDNAs on high density filters (about 31,000 different cDNAs can be spotted currently in duplicates on one filter [28]). Short synthetic DNA sequences, typically 7-12 base... |

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Citation Context ...ber of probes (i.e., oligos) is p. Probes are assumed to occur along a gene with Poisson distribution with rate . This assumption originally was suggested in [23] and was adopted by other researchers =-=[1, 27, 20]-=-. The probability that an oligo occurrence did not register (false negative probability) is ff. False positive hybridizations are assumed to have Poisson distribution with rate fi. All probe occurrenc... |

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Citation Context ...ber of probes (i.e., oligos) is p. Probes are assumed to occur along a gene with Poisson distribution with rate . This assumption originally was suggested in [23] and was adopted by other researchers =-=[1, 27, 20]-=-. The probability that an oligo occurrence did not register (false negative probability) is ff. False positive hybridizations are assumed to have Poisson distribution with rate fi. All probe occurrenc... |

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Citation Context ...vable results on the clustering quality. In particular these algorithms do not guarantee that clusters have diameter two, a key property of our clustering. For other limitations of these methods, see =-=[9]-=-. For the specific problem of clustering cDNA fingerprints, several approaches were suggested previously: Drmanac et al. [28] build clusters around connected components in the similarity graph. In tha... |

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expression profiles in normal and cancer cells
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