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puma 3.0: improved uncertainty propagation methods for gene and transcript expression analysis

BACKGROUND: Microarrays have been a popular tool for gene expression profiling at genome-scale for over a decade due to the low cost, short turn-around time, excellent quantitative accuracy and ease of data generation. The Bioconductor package puma incorporates a suite of analysis methods for determ...

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Autores principales: Liu, Xuejun, Gao, Zhenzhu, Zhang, Li, Rattray, Magnus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3626802/
https://www.ncbi.nlm.nih.gov/pubmed/23379655
http://dx.doi.org/10.1186/1471-2105-14-39
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author Liu, Xuejun
Gao, Zhenzhu
Zhang, Li
Rattray, Magnus
author_facet Liu, Xuejun
Gao, Zhenzhu
Zhang, Li
Rattray, Magnus
author_sort Liu, Xuejun
collection PubMed
description BACKGROUND: Microarrays have been a popular tool for gene expression profiling at genome-scale for over a decade due to the low cost, short turn-around time, excellent quantitative accuracy and ease of data generation. The Bioconductor package puma incorporates a suite of analysis methods for determining uncertainties from Affymetrix GeneChip data and propagating these uncertainties to downstream analysis. As isoform level expression profiling receives more and more interest within genomics in recent years, exon microarray technology offers an important tool to quantify expression level of the majority of exons and enables the possibility of measuring isoform level expression. However, puma does not include methods for the analysis of exon array data. Moreover, the current expression summarisation method for Affymetrix 3’ GeneChip data suffers from instability for low expression genes. For the downstream analysis, the method for differential expression detection is computationally intensive and the original expression clustering method does not consider the variance across the replicated technical and biological measurements. It is therefore necessary to develop improved uncertainty propagation methods for gene and transcript expression analysis. RESULTS: We extend the previously developed Bioconductor package puma with a new method especially designed for GeneChip Exon arrays and a set of improved downstream approaches. The improvements include: (i) a new gamma model for exon arrays which calculates isoform and gene expression measurements and a level of uncertainty associated with the estimates, using the multi-mappings between probes, isoforms and genes, (ii) a variant of the existing approach for the probe-level analysis of Affymetrix 3’ GeneChip data to produce more stable gene expression estimates, (iii) an improved method for detecting differential expression which is computationally more efficient than the existing approach in the package and (iv) an improved method for robust model-based clustering of gene expression, which takes technical and biological replicate information into consideration. CONCLUSIONS: With the extensions and improvements, the puma package is now applicable to the analysis of both Affymetrix 3’ GeneChips and Exon arrays for gene and isoform expression estimation. It propagates the uncertainty of expression measurements into more efficient and comprehensive downstream analysis at both gene and isoform level. Downstream methods are also applicable to other expression quantification platforms, such as RNA-Seq, when uncertainty information is available from expression measurements. puma is available through Bioconductor and can be found at http://www.bioconductor.org.
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spelling pubmed-36268022013-04-24 puma 3.0: improved uncertainty propagation methods for gene and transcript expression analysis Liu, Xuejun Gao, Zhenzhu Zhang, Li Rattray, Magnus BMC Bioinformatics Software BACKGROUND: Microarrays have been a popular tool for gene expression profiling at genome-scale for over a decade due to the low cost, short turn-around time, excellent quantitative accuracy and ease of data generation. The Bioconductor package puma incorporates a suite of analysis methods for determining uncertainties from Affymetrix GeneChip data and propagating these uncertainties to downstream analysis. As isoform level expression profiling receives more and more interest within genomics in recent years, exon microarray technology offers an important tool to quantify expression level of the majority of exons and enables the possibility of measuring isoform level expression. However, puma does not include methods for the analysis of exon array data. Moreover, the current expression summarisation method for Affymetrix 3’ GeneChip data suffers from instability for low expression genes. For the downstream analysis, the method for differential expression detection is computationally intensive and the original expression clustering method does not consider the variance across the replicated technical and biological measurements. It is therefore necessary to develop improved uncertainty propagation methods for gene and transcript expression analysis. RESULTS: We extend the previously developed Bioconductor package puma with a new method especially designed for GeneChip Exon arrays and a set of improved downstream approaches. The improvements include: (i) a new gamma model for exon arrays which calculates isoform and gene expression measurements and a level of uncertainty associated with the estimates, using the multi-mappings between probes, isoforms and genes, (ii) a variant of the existing approach for the probe-level analysis of Affymetrix 3’ GeneChip data to produce more stable gene expression estimates, (iii) an improved method for detecting differential expression which is computationally more efficient than the existing approach in the package and (iv) an improved method for robust model-based clustering of gene expression, which takes technical and biological replicate information into consideration. CONCLUSIONS: With the extensions and improvements, the puma package is now applicable to the analysis of both Affymetrix 3’ GeneChips and Exon arrays for gene and isoform expression estimation. It propagates the uncertainty of expression measurements into more efficient and comprehensive downstream analysis at both gene and isoform level. Downstream methods are also applicable to other expression quantification platforms, such as RNA-Seq, when uncertainty information is available from expression measurements. puma is available through Bioconductor and can be found at http://www.bioconductor.org. BioMed Central 2013-02-05 /pmc/articles/PMC3626802/ /pubmed/23379655 http://dx.doi.org/10.1186/1471-2105-14-39 Text en Copyright © 2013 Liu 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
Liu, Xuejun
Gao, Zhenzhu
Zhang, Li
Rattray, Magnus
puma 3.0: improved uncertainty propagation methods for gene and transcript expression analysis
title puma 3.0: improved uncertainty propagation methods for gene and transcript expression analysis
title_full puma 3.0: improved uncertainty propagation methods for gene and transcript expression analysis
title_fullStr puma 3.0: improved uncertainty propagation methods for gene and transcript expression analysis
title_full_unstemmed puma 3.0: improved uncertainty propagation methods for gene and transcript expression analysis
title_short puma 3.0: improved uncertainty propagation methods for gene and transcript expression analysis
title_sort puma 3.0: improved uncertainty propagation methods for gene and transcript expression analysis
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3626802/
https://www.ncbi.nlm.nih.gov/pubmed/23379655
http://dx.doi.org/10.1186/1471-2105-14-39
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