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Content-based search of gene expression databases using binary fingerprints of differential expression profiles

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Abstract

Availability and rapid growth of microarray databases have made an integrated analysis of these databases computationally challenging. We present a novel approach to content-based searching in microarray databases, using binary vector representations, that is inspired from the Chemoinformatics field. A benchmark compendium of microarray datasets is established for evaluation of content-based searching. Differential expression profiles from microarray experiments are represented either as floating point vectors or as concise binary vectors. The benchmark compendium is searched using several distance measures for determining similarity. We demonstrate that the use of binary vector representations achieves accuracies equivalent to or better than the use of floating point measures, while at the same time significantly reducing the time required to search a microarray database, owing to the fast bitwise operations and the reduction in memory requirements. Experiments on a large database of binary vector representations demonstrate that a modified Tanimoto distance measure is best suited for content-based search of differential microarray profiles. The search method is available as a web service at: http://sacan.biomed.drexel.edu/mageoindex/.

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Abbreviations

GEO:

Gene Expression Omnibus

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Authors and Affiliations

  1. School of Biomedical Engineering, Drexel University, Philadelphia, USA

    Francis Bell & Ahmet Sacan

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  1. Francis Bell
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  2. Ahmet Sacan
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Correspondence to Ahmet Sacan.

Electronic supplementary material

Below is the link to the electronic supplementary material.

13721_2015_76_MOESM1_ESM.doc

Supplementary material 1 Validation Data Sets. Lists the profiles from which subsets were derived for validation. Also includes which samples are included in which subsets. (DOC 132 kb)

13721_2015_76_MOESM2_ESM.xlsx

Supplementary material 2 Results of Confirmation. A spread sheet containing results for confirmation for Hamming, Modified Tanimoto, and Tanimoto distance measure. (XLSX 45 kb)

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Bell, F., Sacan, A. Content-based search of gene expression databases using binary fingerprints of differential expression profiles. Netw Model Anal Health Inform Bioinforma 4, 4 (2015). https://doi.org/10.1007/s13721-015-0076-3

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  • DOI: https://doi.org/10.1007/s13721-015-0076-3

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