Dataset Information

Selecting Reliable mRNA Expression Measurements Across Platforms Improves Downstream Analysis.

ABSTRACT: With increasing use of publicly available gene expression data sets, the quality of the expression data is a critical issue for downstream analysis, gene signature development, and cross-validation of data sets. Thus, identifying reliable expression measurements by leveraging multiple mRNA expression platforms is an important analytical task. In this study, we propose a statistical framework for selecting reliable measurements between platforms by modeling the correlations of mRNA expression levels using a beta-mixture model. The model-based selection provides an effective and objective way to separate good probes from probes with low quality, thereby improving the efficiency and accuracy of the analysis. The proposed method can be used to compare two microarray technologies or microarray and RNA sequencing measurements. We tested the approach in two matched profiling data sets, using microarray gene expression measurements from the same samples profiled on both Affymetrix and Illumina platforms. We also applied the algorithm to mRNA expression data to compare Affymetrix microarray data with RNA sequencing measurements. The algorithm successfully identified probes/genes with reliable measurements. Removing the unreliable measurements resulted in significant improvements for gene signature development and functional annotations.

SUBMITTER: Tong P

PROVIDER: S-EPMC4863871 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Selecting Reliable mRNA Expression Measurements Across Platforms Improves Downstream Analysis.

Tong Pan P Diao Lixia L Shen Li L Li Lerong L Heymach John Victor JV Girard Luc L Minna John D JD Coombes Kevin R KR Byers Lauren Averett LA Wang Jing J

Cancer informatics 20160510

With increasing use of publicly available gene expression data sets, the quality of the expression data is a critical issue for downstream analysis, gene signature development, and cross-validation of data sets. Thus, identifying reliable expression measurements by leveraging multiple mRNA expression platforms is an important analytical task. In this study, we propose a statistical framework for selecting reliable measurements between platforms by modeling the correlations of mRNA expression lev ...[more]

PMID: 27199546

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Project description:Intensive cultivation of freshwater macroalgae is likely to increase with the development of an algal biofuels industry and algal bioremediation. However, target freshwater macroalgae species suitable for large-scale intensive cultivation have not yet been identified. Therefore, as a first step to identifying target species, we compared the productivity, growth and biochemical composition of three species representative of key freshwater macroalgae genera across a range of cultivation conditions. We then selected a primary target species and assessed its competitive ability against other species over a range of stocking densities. Oedogonium had the highest productivity (8.0 g ash free dry weight m⁻² day⁻¹), lowest ash content (3-8%), lowest water content (fresh weigh: dry weight ratio of 3.4), highest carbon content (45%) and highest bioenergy potential (higher heating value 20 MJ/kg) compared to Cladophora and Spirogyra. The higher productivity of Oedogonium relative to Cladophora and Spirogyra was consistent when algae were cultured with and without the addition of CO₂ across three aeration treatments. Therefore, Oedogonium was selected as our primary target species. The competitive ability of Oedogonium was assessed by growing it in bi-cultures and polycultures with Cladophora and Spirogyra over a range of stocking densities. Cultures were initially stocked with equal proportions of each species, but after three weeks of growth the proportion of Oedogonium had increased to at least 96% (±7 S.E.) in Oedogonium-Spirogyra bi-cultures, 86% (±16 S.E.) in Oedogonium-Cladophora bi-cultures and 82% (±18 S.E.) in polycultures. The high productivity, bioenergy potential and competitive dominance of Oedogonium make this species an ideal freshwater macroalgal target for large-scale production and a valuable biomass source for bioenergy applications. These results demonstrate that freshwater macroalgae are thus far an under-utilised feedstock with much potential for biomass applications.

Dataset Information

Selecting Reliable mRNA Expression Measurements Across Platforms Improves Downstream Analysis.

Publications

Selecting Reliable mRNA Expression Measurements Across Platforms Improves Downstream Analysis.

Similar Datasets

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