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For inter-assay calibration, we used the same selected positive serum samples in all applications.
This resulted in an initial set of 2,206,307 possible 1.5 kb windows, for which we used the same selected chromatin features as for the intergenic enhancers.
For the *BEAST analysis we used the same selected models and additionally a variety of models which are *BEAST-specific, such as the relaxed clock model.
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Multiple logistic regression modeling (MLR) was performed using the same selected risk variables or features and case status (as specified previously and in Table 1) as the outcome variable.
We used the same selection criteria for selecting our sequences where more than one sequence was available for a gene within a given clade.
All of the models were fitted using the same explanatory and dependent variables, and they used the same randomly selected training samples.
If no data were available, we used the same equations selected for other countries and similar forest types (FTs, defined according to the main species).
T2 transgenic plants were selected using the same selection method and positive transformants were used in further analysis.
All the selective test cases used the same 1,000 snapshots selected from the InhA-NADH results and, as the exhaustive test cases, for simplicity, considered the ligands rigid.
In 2005, 2006, and 2007, we used the same method to select households within the selected villages.
We used the same tagging SNPs selected for a CTS-nested case-control study of breast cancer [ 29].
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