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Exploiting the bootstrap method to analyze patterns of gene expression

Background

High-throughput technologies like microarrays or the recent RNA-Seq provide large amounts of data for gene expression studies. Although there have been diverse methods to design gene-expression experiments and analyze gene-expression data, the prediction of true patterns of gene expression in case of having few samples remains a challenging problem [1, 2].

Materials and methods

We propose a method to predict response patterns of gene expression studies in the case of small sample size using a bootstrap method [3]. Our approach adopts partially order sets (posets) to represent gene patterns, which are determined based on pairwise comparisons [4].

Results

We show that patterns that are not linearly orderable cannot be true patterns of gene response to treatments. From this result, we propose a strategy using bootstrap resampling to infer true responses of non-linearly-orderable patterns. Our experiments showed that this method produced gene lists with more biological functional enrichment than those obtained without bootstrap resampling.

Conclusions

Our method is useful in designing cost-effective experiments with small sample sizes. Researchers can still use a small sample size to determine true patterns for most genes. For highly-variantly expressed genes, their true patterns can be identified using the proposed method.

References

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  3. Davison AC, Hinkey DV: Bootstrap methods and their application. Cambridge Series in Statistical and Probabilistic Mathematics. 1997, New York: Cambridge University Press, 1:

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  4. Vo N, Phan V: Exploiting dependencies of patterns in gene expression analysis using pairwise comparisons. Lecture Notes in Computer Science, Bioinformatics Research and Applications. Edited by: Cai Z, Eulenstein O, Janies D, Schwartz D. 2013, Berlin: Springer, 7875: 173-184. 10.1007/978-3-642-38036-5_19.

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Acknowledgements

This work is partly supported by NSF CCF-1320297.

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Correspondence to Nam S Vo.

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This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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Vo, N.S., Phan, V. Exploiting the bootstrap method to analyze patterns of gene expression. BMC Bioinformatics 15 (Suppl 10), P19 (2014). https://doi.org/10.1186/1471-2105-15-S10-P19

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  • DOI: https://doi.org/10.1186/1471-2105-15-S10-P19

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