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We categorized samples in multiple breast cancer data sets by PAM50 gene signature (Parker et al., 2009).
We categorized samples into three groups: 1) <33% methylation (hypomethylated), 2) 33-66% methylation (median methylation), and 3) >66% methylation (hypermethylation) as previously described [ 11, 26].
Additionally, electronic tracking of the methodically categorized samples is essential for swift retrieval of those that are suitable for a specific request among the ones kept in freezers.
PAH DNA adducts were categorized as detectable or nondetectable; for analytical purposes, we categorized samples with < 15% inhibition as nondetectable (Gammon et al. 2002b).
We further categorized samples according to whether they were sold as lean red tuna (akami in Japanese) or fatty tuna (toro) because mercury and lipid concentrations are inversely proportional in tuna (Balshaw et al. 2008 a ).
We categorized samples with mean membership probability of >0.6 to one of the clusters as 'pure' samples (for use in the outlier tests and LD analyses) and the others as 'mixed' samples.
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The first analysis was descriptive, and categorized sample respondents by demographics, socioeconomics and clinical characteristics and compared respondents in underweight, normal, overweight and obese BMI categories.
Based on recommendations from regulatory agencies for safety assessment [ 11, 12, 16, 17], we categorized sample sizes into six levels: 1) < 100 patients; 2) 100 to 299 patients; 3) 300 to 599 patients; 4) 600 to 1499 patients; 5) 1500 to 5000 and 6) > 5000 patients.
Standard clinical lab cut-off points were used to categorize samples as positive or negative.
Standard clinical lab cutoff points were used to categorize samples as positive or negative.
To categorize samples by test results, we applied the rules shown in Figure 1.
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CEO of Professional Science Editing for Scientists @ prosciediting.com