Sentence examples for single marker testing from inspiring English sources

Penalized regression methods offer an attractive alternative to single marker testing in genetic association analysis.

We defined the unadjusted power for single marker testing methods as the proportion of replicates with minimum p-values < =0.05.

We noticed that single marker testing was not as efficient as methods that jointly analyze a group of mutations such as CMC, WSS and VT.

Some studies had demonstrated that CMC, WSS and VT would encounter the loss of power when the direction of effects in the combined variants is not consistent, or when a small fraction of variants are associated with disease, as compared to single marker testing [ 39, 40].

© 2010 Wiley-Liss, Inc. Regression methods are commonly used in statistical analysis, and the recent move to single marker testing in genetic association studies [WTCCC, 2007] has been out of necessity on account of the large number of predictor variables (upwards of 500,000 genetic markers) to be examined.

This study demonstrates that testing 3 molecular markers (c-Ki-ras, p53 and c-erbB-2) improves estimation of prognosis compared to single marker testing and appears to define low (82.6% ± 7.9% 5-year survival) and high risk (40.2% ± 5.5% 5-year survival) groups for treatment failure in potentially curative (RO) resected NSCLC.

Our simulation results indicate substantial gain in power using LGRF when compared with two commonly used existing alternatives: (i) single marker tests using longitudinal outcome and (ii) existing gene-based tests using the average value of repeated measurements as the outcome.

We explore, in a two-stage design, how the use of false discovery rate (FDR) can alleviate the burden of a prohibitively strict significance level for single marker tests and still control the number of false positive findings, when there is more than one causal variant.

Compared with single marker tests, such as D-dimer, a multi-marker strategy may improve diagnostic ability.

Previous studies have shown that single marker tests provide similar or greater power than haplotype-based approaches [57], [58].

Second, we applied the false discovery rate to quantify uncertainty across the multiple hypotheses tested in the six single marker tests and the multiple haplotype tests.