Pixel-level signal modelling with spatial correlation for two-colour microarrays

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Standard

Pixel-level signal modelling with spatial correlation for two-colour microarrays. / Ekstrøm, Claus T.; Bak, Søren; Rudemo, Mats.

In: Statistical Applications in Genetics and Molecular Biology, Vol. 4, No. 1, 6, 06.04.2005.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Ekstrøm, CT, Bak, S & Rudemo, M 2005, 'Pixel-level signal modelling with spatial correlation for two-colour microarrays', Statistical Applications in Genetics and Molecular Biology, vol. 4, no. 1, 6. https://doi.org/10.2202/1544-6115.1112

APA

Ekstrøm, C. T., Bak, S., & Rudemo, M. (2005). Pixel-level signal modelling with spatial correlation for two-colour microarrays. Statistical Applications in Genetics and Molecular Biology, 4(1), [6]. https://doi.org/10.2202/1544-6115.1112

Vancouver

Ekstrøm CT, Bak S, Rudemo M. Pixel-level signal modelling with spatial correlation for two-colour microarrays. Statistical Applications in Genetics and Molecular Biology. 2005 Apr 6;4(1). 6. https://doi.org/10.2202/1544-6115.1112

Author

Ekstrøm, Claus T. ; Bak, Søren ; Rudemo, Mats. / Pixel-level signal modelling with spatial correlation for two-colour microarrays. In: Statistical Applications in Genetics and Molecular Biology. 2005 ; Vol. 4, No. 1.

Bibtex

@article{929766bfc85a4de6ac6d0929457ead4e,
title = "Pixel-level signal modelling with spatial correlation for two-colour microarrays",
abstract = "Statistical models for spot shapes and signal intensities are used in image analysis of laser scans of microarrays. Most models have essentially been based on the assumption of independent pixel intensity values, but models that allow for spatial correlation among neighbouring pixels can accommodate errors in the microarray slide and should improve the model fit. Five spatial correlation structures, exponential, Gaussian, linear, rational quadratic and spherical, are compared for a dataset with 50-mer two-colour oligonucleotide microarrays and 452 probes for selected Arabidopsis genes. Substantial improvement in model fit is obtained for all five correlation structures compared to the model with independent pixel values, and the Gaussian and the spherical models seem to be slightly better than the other three models. We also conclude that for the data set analysed the correlation seems negligible for non-neighbouring pixels.",
keywords = "Censored data, Polynomial-hyperbolic model, Spatial correlation, Spotted array",
author = "Ekstr{\o}m, {Claus T.} and S{\o}ren Bak and Mats Rudemo",
year = "2005",
month = apr,
day = "6",
doi = "10.2202/1544-6115.1112",
language = "English",
volume = "4",
journal = "Statistical Applications in Genetics and Molecular Biology",
issn = "1544-6115",
publisher = "Walterde Gruyter GmbH",
number = "1",

}

RIS

TY - JOUR

T1 - Pixel-level signal modelling with spatial correlation for two-colour microarrays

AU - Ekstrøm, Claus T.

AU - Bak, Søren

AU - Rudemo, Mats

PY - 2005/4/6

Y1 - 2005/4/6

N2 - Statistical models for spot shapes and signal intensities are used in image analysis of laser scans of microarrays. Most models have essentially been based on the assumption of independent pixel intensity values, but models that allow for spatial correlation among neighbouring pixels can accommodate errors in the microarray slide and should improve the model fit. Five spatial correlation structures, exponential, Gaussian, linear, rational quadratic and spherical, are compared for a dataset with 50-mer two-colour oligonucleotide microarrays and 452 probes for selected Arabidopsis genes. Substantial improvement in model fit is obtained for all five correlation structures compared to the model with independent pixel values, and the Gaussian and the spherical models seem to be slightly better than the other three models. We also conclude that for the data set analysed the correlation seems negligible for non-neighbouring pixels.

AB - Statistical models for spot shapes and signal intensities are used in image analysis of laser scans of microarrays. Most models have essentially been based on the assumption of independent pixel intensity values, but models that allow for spatial correlation among neighbouring pixels can accommodate errors in the microarray slide and should improve the model fit. Five spatial correlation structures, exponential, Gaussian, linear, rational quadratic and spherical, are compared for a dataset with 50-mer two-colour oligonucleotide microarrays and 452 probes for selected Arabidopsis genes. Substantial improvement in model fit is obtained for all five correlation structures compared to the model with independent pixel values, and the Gaussian and the spherical models seem to be slightly better than the other three models. We also conclude that for the data set analysed the correlation seems negligible for non-neighbouring pixels.

KW - Censored data

KW - Polynomial-hyperbolic model

KW - Spatial correlation

KW - Spotted array

UR - http://www.scopus.com/inward/record.url?scp=84860945403&partnerID=8YFLogxK

U2 - 10.2202/1544-6115.1112

DO - 10.2202/1544-6115.1112

M3 - Journal article

AN - SCOPUS:84860945403

VL - 4

JO - Statistical Applications in Genetics and Molecular Biology

JF - Statistical Applications in Genetics and Molecular Biology

SN - 1544-6115

IS - 1

M1 - 6

ER -

ID: 203909627