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To estimate the relative difference in gene expression between samples, we assumed that the efficiency of amplification was 90%, a typical value [ 59, 60].
One locus pair, Cgu21 and Cgu26, was in significant linkage disequilibrium in Elephant Island after correction, but given that these loci did not show corresponding disequilibria in other samples, we assumed that the loci were not physically linked.
In analyzing the paired samples, we assumed that the majority of proteins would not substantially change in their relative levels and that, as such, the ratio for most proteins would remain at 1.0.
To detect possible genetic bottlenecks (i.e. significant heterozygote excess) in any of the analyzed population samples, we assumed the SMM, IAM, and TPM, and applied the Wilcoxon sign-rank test as implemented in the software BOTTLENECK [ 80].
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The sample versions of these matrices are nonsingular, but in large samples we assume these sample matrices converge to a singular matrix.
To adapt this algorithm for gene expression analysis, we inverted the original question here by asking, "in how many samples from the same body part is a gene X expressed above a fixed cut-off threshold?" Since the index is determined as a robust proportion of outlying samples, we assume that every gene is represented by an adequate number of samples.
Additionally, to model diploid samples, we assume that if one of the two chromosomes in a diploid individual is in the panel of most diverse haplotypes, both chromosomes are sequenced.
Since all heath care facilities were included in the sample, we assumed a design effect of 1.
Because of the limited size of the sample, we assumed that assortative mating, genetic inheritance, shared environmental influences, and CT remain constant from generation to generation.
Given the left-right symmetry of PrPSc distribution, which was verified by IHC analysis of the adjacent rostral and caudal coronal levels of the selected sample, we assumed that titer did not vary substantially on either side of the midline.
With regard to the second aim, when comparing high school students (non-clinical sample) with adolescent patients (clinical social anxiety disorder sample), we assumed that the patients would have significantly higher scores on all scales of the SASKO-J than the students.
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