Volume 127, Issue 21 pp. 6437-6440
Zuschrift

Next-Generation Sequencing as Input for Chemometrics in Differential Sensing Routines

Sara Goodwin

Sara Goodwin

Cold Spring Harbor Laboratory, Cold Spring Harbor, NY (USA)

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Alexandra M. Gade

Alexandra M. Gade

Department of Chemistry A1590, The University of Texas at Austin, Austin, TX 78712 (USA)

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Michelle Byrom

Michelle Byrom

Institute for Cell and Molecular Biology, The University of Texas at Austin, Austin, TX 78712 (USA)

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Baine Herrera

Baine Herrera

Institute for Cell and Molecular Biology, The University of Texas at Austin, Austin, TX 78712 (USA)

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Camille Spears

Camille Spears

Institute for Cell and Molecular Biology, The University of Texas at Austin, Austin, TX 78712 (USA)

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Dr. Eric V. Anslyn

Corresponding Author

Dr. Eric V. Anslyn

Department of Chemistry A1590, The University of Texas at Austin, Austin, TX 78712 (USA)

Eric V. Anslyn, Department of Chemistry A1590, The University of Texas at Austin, Austin, TX 78712 (USA)

Andrew D. Ellington, Institute for Cell and Molecular Biology, The University of Texas at Austin, Austin, TX 78712 (USA)

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Dr. Andrew D. Ellington

Corresponding Author

Dr. Andrew D. Ellington

Institute for Cell and Molecular Biology, The University of Texas at Austin, Austin, TX 78712 (USA)

Eric V. Anslyn, Department of Chemistry A1590, The University of Texas at Austin, Austin, TX 78712 (USA)

Andrew D. Ellington, Institute for Cell and Molecular Biology, The University of Texas at Austin, Austin, TX 78712 (USA)

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First published: 31 March 2015
Citations: 3

We gratefully acknowledge support from both the NIH (R01-GM065515) and the Welch Foundation (F.1151).

Abstract

Differential sensing (DS) methods traditionally use spatially arrayed receptors and optical signals to create score plots from multivariate data which classify individual analytes or complex mixtures. Herein, a new approach is described, in which nucleic acid sequences and sequence counts are used as the multivariate data without the necessity of a spatial array. To demonstrate this approach to DS, previously selected aptamers, identified from the literature, were used as semi-specific receptors, Next-Gen DNA sequencing was used to generate data, and cell line differentiation was the test-bed application. The study of a principal component analysis loading plot revealed cross-reactivity between the aptamers. The technique generates high-dimensionality score plots, and should be applicable to any mixture of complex and subtly different analytes for which nucleic acid-based receptors exist.

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