The information ratio is almost 1 thus most of the information is stored in the residual space. Predictor accuracy The correlation between the IR and the potential accuracy of a predictor was evaluated. Every day, thousands of employers search Indeed. This apparent doubling of complexity yields additional insights into the information contained in the genomic data. How does Europe PMC derive its citations network? The information may reside mainly in the residual space, mainly in the projected space, or somewhere in between. Upload your resume Sign in.

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The following section presents the results of the analysis of several publicly available microarray datasets.

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The weights, w ifor each gene i guarantee that the genes with high sensitivity contribute more to IR than genes with low sensitivity. Depending on the phenotype the information is distributed differently between the subspace and the residual space. It is important to understand and gauge the stability of gene lists across different studies. We demonstrate that the IR is indicative of biomarker stability: Additional file 2 Figure S1.

The projection lp p blue crosses onto S n shows very low absolute values compared to the residuals lp r red crosses. Easily apply 9 days ago – save job – more For classification of clinical samples based on microarray data, prediction is usually performed with a gene list, a subset of all available genes.

The x-axis shows p-values of differential gene expression in the original data, while the y-axis shows p-values for projected blue and residual red data. Additional file 3 Workflow.


Quantifying stability in gene list ranking across microarray derived clinical biomarkers

This gene list was then used to train an SVM for each study with default parameters. This article has been cited by other articles in PMC. We denote the space, spanned by the first n eigenvectors, as S n. Across all studies, symbols were shared and only those were used for further analysis. Gene expression profiles do not consistently predict the clinical treatment response in locally advanced breast cancer. Moreover, the qualitative heterogeneity of the genome-wide information distribution across different studies for high IR phenotypes indicate that biomarkers which are identified using ranked gene lists, will most likely not be predictive through statistical approaches alone.

In order to suppress false results from genes with low overall differential expression, the IR is calculated as weighted sum of p-value ratios:. The information ratio is almost 1 thus most of the information is stored in the residual space. In turn, each study was used to derive a gene list, and this list was evaluated with all the other studies.

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Seattle, Washington – Column Group. Consequently, the ranking of gene lists depends strongly on the individual study and is not easily transferable between studies.

The IR and predictor accuracy The IR is a suitable indicator for gene list stability, with a high IR being indicative of a stable gene list. A bjc of bcm expression data was generated with dimensionality between 1 and If one study is used to derive a gene list, and this gene list is used to build a classifier for another study, a decrease in accuracy can be observed.


Each eigenvector k represents a metagene whose expression X k, l in each tissue l is given by the weighted sum of the contribution of all genes j to the eigenvector: To calculate the intrinsic weight distribution, wwe observed that the distribution of the genomic log 10 p-values with respect to almost all physiological factors satisfy an exponential distribution Figures 8a, b.

Such analyses are then critical to understanding cellular physiology, clinical phenotypes and for predicting the efficacy of drugs on diseased cells. Observe that the p-values are high compared to the other cases. Here we present a method to demonstrate that gene list stability and predictive power depends not only on the size of studies, but also on the clinical phenotype.

Be the first to see new Lightspeed Technology Group jobs My email: This allowed for a total of 87 pair-wise comparisons between studies regarding a specific phenotype. Results from microarray experiments can be arranged as an n by p matrix with n being the number of samples and p the number of measured features or probesets. The bm to identify stable tumor prognosis and predictive outcome markers remains critical in clinical 994306 research.

Thus, biomarkers may be identified to discriminate between phenotypes among the low IR values.

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