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Analysis of tiling array expression studies with flexible designs in Bioconductor (waveTiling)

BACKGROUND: Existing statistical methods for tiling array transcriptome data either focus on transcript discovery in one biological or experimental condition or on the detection of differential expression between two conditions. Increasingly often, however, biologists are interested in time-course s...

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Autores principales: Beuf, Kristof De, Pipelers, Peter, Andriankaja, Megan, Thas, Olivier, Inzé, Dirk, Crainiceanu, Ciprian, Clement, Lieven
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3558343/
https://www.ncbi.nlm.nih.gov/pubmed/22974078
http://dx.doi.org/10.1186/1471-2105-13-234
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author Beuf, Kristof De
Pipelers, Peter
Andriankaja, Megan
Thas, Olivier
Inzé, Dirk
Crainiceanu, Ciprian
Clement, Lieven
author_facet Beuf, Kristof De
Pipelers, Peter
Andriankaja, Megan
Thas, Olivier
Inzé, Dirk
Crainiceanu, Ciprian
Clement, Lieven
author_sort Beuf, Kristof De
collection PubMed
description BACKGROUND: Existing statistical methods for tiling array transcriptome data either focus on transcript discovery in one biological or experimental condition or on the detection of differential expression between two conditions. Increasingly often, however, biologists are interested in time-course studies, studies with more than two conditions or even multiple-factor studies. As these studies are currently analyzed with the traditional microarray analysis techniques, they do not exploit the genome-wide nature of tiling array data to its full potential. RESULTS: We present an R Bioconductor package, waveTiling, which implements a wavelet-based model for analyzing transcriptome data and extends it towards more complex experimental designs. With waveTiling the user is able to discover (1) group-wise expressed regions, (2) differentially expressed regions between any two groups in single-factor studies and in (3) multifactorial designs. Moreover, for time-course experiments it is also possible to detect (4) linear time effects and (5) a circadian rhythm of transcripts. By considering the expression values of the individual tiling probes as a function of genomic position, effect regions can be detected regardless of existing annotation. Three case studies with different experimental set-ups illustrate the use and the flexibility of the model-based transcriptome analysis. CONCLUSIONS: The waveTiling package provides the user with a convenient tool for the analysis of tiling array trancriptome data for a multitude of experimental set-ups. Regardless of the study design, the probe-wise analysis allows for the detection of transcriptional effects in both exonic, intronic and intergenic regions, without prior consultation of existing annotation.
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spelling pubmed-35583432013-01-31 Analysis of tiling array expression studies with flexible designs in Bioconductor (waveTiling) Beuf, Kristof De Pipelers, Peter Andriankaja, Megan Thas, Olivier Inzé, Dirk Crainiceanu, Ciprian Clement, Lieven BMC Bioinformatics Software BACKGROUND: Existing statistical methods for tiling array transcriptome data either focus on transcript discovery in one biological or experimental condition or on the detection of differential expression between two conditions. Increasingly often, however, biologists are interested in time-course studies, studies with more than two conditions or even multiple-factor studies. As these studies are currently analyzed with the traditional microarray analysis techniques, they do not exploit the genome-wide nature of tiling array data to its full potential. RESULTS: We present an R Bioconductor package, waveTiling, which implements a wavelet-based model for analyzing transcriptome data and extends it towards more complex experimental designs. With waveTiling the user is able to discover (1) group-wise expressed regions, (2) differentially expressed regions between any two groups in single-factor studies and in (3) multifactorial designs. Moreover, for time-course experiments it is also possible to detect (4) linear time effects and (5) a circadian rhythm of transcripts. By considering the expression values of the individual tiling probes as a function of genomic position, effect regions can be detected regardless of existing annotation. Three case studies with different experimental set-ups illustrate the use and the flexibility of the model-based transcriptome analysis. CONCLUSIONS: The waveTiling package provides the user with a convenient tool for the analysis of tiling array trancriptome data for a multitude of experimental set-ups. Regardless of the study design, the probe-wise analysis allows for the detection of transcriptional effects in both exonic, intronic and intergenic regions, without prior consultation of existing annotation. BioMed Central 2012-09-14 /pmc/articles/PMC3558343/ /pubmed/22974078 http://dx.doi.org/10.1186/1471-2105-13-234 Text en Copyright ©2012 De Beuf et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software
Beuf, Kristof De
Pipelers, Peter
Andriankaja, Megan
Thas, Olivier
Inzé, Dirk
Crainiceanu, Ciprian
Clement, Lieven
Analysis of tiling array expression studies with flexible designs in Bioconductor (waveTiling)
title Analysis of tiling array expression studies with flexible designs in Bioconductor (waveTiling)
title_full Analysis of tiling array expression studies with flexible designs in Bioconductor (waveTiling)
title_fullStr Analysis of tiling array expression studies with flexible designs in Bioconductor (waveTiling)
title_full_unstemmed Analysis of tiling array expression studies with flexible designs in Bioconductor (waveTiling)
title_short Analysis of tiling array expression studies with flexible designs in Bioconductor (waveTiling)
title_sort analysis of tiling array expression studies with flexible designs in bioconductor (wavetiling)
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3558343/
https://www.ncbi.nlm.nih.gov/pubmed/22974078
http://dx.doi.org/10.1186/1471-2105-13-234
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