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Systematic evaluation of three microRNA profiling platforms: microarray, beads array, and quantitative real-time PCR array.

Wang B, Howel P, Bruheim S, Ju J, Owen LB, Fodstad O, Xi Y - PLoS ONE (2011)

Bottom Line: Results show that each of the three platforms perform similarly regarding intra-platform reproducibility or reproducibility of data within one platform while LNA array and TLDA had the best inter-platform reproducibility or reproducibility of data across platforms.Each platform is relatively stable in terms of its own microRNA profiling intra-reproducibility; however, the inter-platform reproducibility among different platforms is low.More microRNA specific normalization methods are in demand for cross-platform microRNA microarray data integration and comparison, which will improve the reproducibility and consistency between platforms.

View Article: PubMed Central - PubMed

Affiliation: Department of Mathematics and Statistics, University of South Alabama College of Arts and Sciences, Mobile, Alabama, United States of America.

ABSTRACT

Background: A number of gene-profiling methodologies have been applied to microRNA research. The diversity of the platforms and analytical methods makes the comparison and integration of cross-platform microRNA profiling data challenging. In this study, we systematically analyze three representative microRNA profiling platforms: Locked Nucleic Acid (LNA) microarray, beads array, and TaqMan quantitative real-time PCR Low Density Array (TLDA).

Methodology/principal findings: The microRNA profiles of 40 human osteosarcoma xenograft samples were generated by LNA array, beads array, and TLDA. Results show that each of the three platforms perform similarly regarding intra-platform reproducibility or reproducibility of data within one platform while LNA array and TLDA had the best inter-platform reproducibility or reproducibility of data across platforms. The endogenous controls/probes contained in each platform have been observed for their stability under different treatments/environments; those included in TLDA have the best performance with minimal coefficients of variation. Importantly, we identify that the proper selection of normalization methods is critical for improving the inter-platform reproducibility, which is evidenced by the application of two non-linear normalization methods (loess and quantile) that substantially elevated the sensitivity and specificity of the statistical data assessment.

Conclusions: Each platform is relatively stable in terms of its own microRNA profiling intra-reproducibility; however, the inter-platform reproducibility among different platforms is low. More microRNA specific normalization methods are in demand for cross-platform microRNA microarray data integration and comparison, which will improve the reproducibility and consistency between platforms.

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Intra- and inter-platform reproducibility comparisons.The first box plot to the left is based on Spearman's correlation coefficients between the LNA profiles of any two samples under the same treatment. The second and third plots are for the beads array and TLDA, respectively. The fourth plot is constructed based on the Spearman's correlation coefficients between the two profiles obtained by beads array and LNA array based on the same sample under the same treatment for all 10 samples. The fifth plot shows the results between beads array and TLDA, while the sixth plot shows the results between LNA array and TLDA.
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pone-0017167-g003: Intra- and inter-platform reproducibility comparisons.The first box plot to the left is based on Spearman's correlation coefficients between the LNA profiles of any two samples under the same treatment. The second and third plots are for the beads array and TLDA, respectively. The fourth plot is constructed based on the Spearman's correlation coefficients between the two profiles obtained by beads array and LNA array based on the same sample under the same treatment for all 10 samples. The fifth plot shows the results between beads array and TLDA, while the sixth plot shows the results between LNA array and TLDA.

Mentions: To evaluate the intra-platform reproducibility, we calculated the rank-based Spearman's correlation coefficients among various miRNA profiles tested on different samples by the same platform. A stable platform is expected to produce similar results across different experiments. In other words, the results from the same sample using the same platform should be reproducible. The Pearson correlation coefficient analysis was banned because the study demonstrated that array profiling data were mostly non-linear [23], [24]. By using the Spearman's correlation coefficient measurement to evaluate intra-platform reproducibility, which adopts the rank information, the different scales used in each platform may be ignored and log-transformation can be avoided. From the three box plots on the left in Figure 3, we see that the beads array has the highest intra-platform reproducibility with a median Spearman correlation of 0.8544 and a standard deviation of 0.0475. The first and third quartiles are 0.8189 and 0.8877, respectively. TLDA has a median coefficient of 0.8118 with a standard deviation of 0.0745. The median coefficient of the LNA array is 0.7367, and the standard deviation is 0.0759. The correlation coefficients are computed based on the profiles of 213 overlapping miRNAs that are undergoing the same treatment. Our results demonstrate that the intra-platform reproducibility of all three platforms are acceptable and have no significant differences.


Systematic evaluation of three microRNA profiling platforms: microarray, beads array, and quantitative real-time PCR array.

Wang B, Howel P, Bruheim S, Ju J, Owen LB, Fodstad O, Xi Y - PLoS ONE (2011)

Intra- and inter-platform reproducibility comparisons.The first box plot to the left is based on Spearman's correlation coefficients between the LNA profiles of any two samples under the same treatment. The second and third plots are for the beads array and TLDA, respectively. The fourth plot is constructed based on the Spearman's correlation coefficients between the two profiles obtained by beads array and LNA array based on the same sample under the same treatment for all 10 samples. The fifth plot shows the results between beads array and TLDA, while the sixth plot shows the results between LNA array and TLDA.
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Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3037970&req=5

pone-0017167-g003: Intra- and inter-platform reproducibility comparisons.The first box plot to the left is based on Spearman's correlation coefficients between the LNA profiles of any two samples under the same treatment. The second and third plots are for the beads array and TLDA, respectively. The fourth plot is constructed based on the Spearman's correlation coefficients between the two profiles obtained by beads array and LNA array based on the same sample under the same treatment for all 10 samples. The fifth plot shows the results between beads array and TLDA, while the sixth plot shows the results between LNA array and TLDA.
Mentions: To evaluate the intra-platform reproducibility, we calculated the rank-based Spearman's correlation coefficients among various miRNA profiles tested on different samples by the same platform. A stable platform is expected to produce similar results across different experiments. In other words, the results from the same sample using the same platform should be reproducible. The Pearson correlation coefficient analysis was banned because the study demonstrated that array profiling data were mostly non-linear [23], [24]. By using the Spearman's correlation coefficient measurement to evaluate intra-platform reproducibility, which adopts the rank information, the different scales used in each platform may be ignored and log-transformation can be avoided. From the three box plots on the left in Figure 3, we see that the beads array has the highest intra-platform reproducibility with a median Spearman correlation of 0.8544 and a standard deviation of 0.0475. The first and third quartiles are 0.8189 and 0.8877, respectively. TLDA has a median coefficient of 0.8118 with a standard deviation of 0.0745. The median coefficient of the LNA array is 0.7367, and the standard deviation is 0.0759. The correlation coefficients are computed based on the profiles of 213 overlapping miRNAs that are undergoing the same treatment. Our results demonstrate that the intra-platform reproducibility of all three platforms are acceptable and have no significant differences.

Bottom Line: Results show that each of the three platforms perform similarly regarding intra-platform reproducibility or reproducibility of data within one platform while LNA array and TLDA had the best inter-platform reproducibility or reproducibility of data across platforms.Each platform is relatively stable in terms of its own microRNA profiling intra-reproducibility; however, the inter-platform reproducibility among different platforms is low.More microRNA specific normalization methods are in demand for cross-platform microRNA microarray data integration and comparison, which will improve the reproducibility and consistency between platforms.

View Article: PubMed Central - PubMed

Affiliation: Department of Mathematics and Statistics, University of South Alabama College of Arts and Sciences, Mobile, Alabama, United States of America.

ABSTRACT

Background: A number of gene-profiling methodologies have been applied to microRNA research. The diversity of the platforms and analytical methods makes the comparison and integration of cross-platform microRNA profiling data challenging. In this study, we systematically analyze three representative microRNA profiling platforms: Locked Nucleic Acid (LNA) microarray, beads array, and TaqMan quantitative real-time PCR Low Density Array (TLDA).

Methodology/principal findings: The microRNA profiles of 40 human osteosarcoma xenograft samples were generated by LNA array, beads array, and TLDA. Results show that each of the three platforms perform similarly regarding intra-platform reproducibility or reproducibility of data within one platform while LNA array and TLDA had the best inter-platform reproducibility or reproducibility of data across platforms. The endogenous controls/probes contained in each platform have been observed for their stability under different treatments/environments; those included in TLDA have the best performance with minimal coefficients of variation. Importantly, we identify that the proper selection of normalization methods is critical for improving the inter-platform reproducibility, which is evidenced by the application of two non-linear normalization methods (loess and quantile) that substantially elevated the sensitivity and specificity of the statistical data assessment.

Conclusions: Each platform is relatively stable in terms of its own microRNA profiling intra-reproducibility; however, the inter-platform reproducibility among different platforms is low. More microRNA specific normalization methods are in demand for cross-platform microRNA microarray data integration and comparison, which will improve the reproducibility and consistency between platforms.

Show MeSH
Related in: MedlinePlus