Evidence map›Paper›PMID 23379655›Full record

ArticleBMC bioinformatics2013

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

Xuejun Liu, Zhenzhu Gao, Li Zhang, Magnus Rattray

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Article in BMC bioinformatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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5citing papers in PubMed
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5 citing papers in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

Xuejun LiuCollege of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, 29 Yudao St., Nanjing 210016, China. xuejun.liu@nuaa.edu.cn
Zhenzhu Gao
Li Zhang
Magnus Rattray

Funding

Biotechnology and Biological Sciences Research Council BB/H018123/2
6 · The paper itself

Abstract

backgroundMicroarrays 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.

resultsWe 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.

conclusionsWith 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.

Indexed as

Oligonucleotide Array Sequence AnalysisSoftwareCarcinoma, Squamous CellCluster AnalysisExonsGene Expression ProfilingGenomicsHead and Neck NeoplasmsHumansRNA IsoformsSquamous Cell Carcinoma of Head and NeckUncertaintyRNA Isoforms

Identifiers

PMID23379655
PMCPMC3626802

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