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The correlations between markers were also generally stronger in ER- cases.
Linkage disequilibrium analyses between markers were also carried out using PLINK.
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Differences in assignment percentages between SSR and SNP markers were also reported by several studies [ 27, 40, 41, 43] and were attributed to the higher information content of SSRs [ 43, 49].
Bivariate associations between the various markers were also analysed.
Double crossovers that occurred between closely adjacent markers were also seen in a number of progeny.
Differences in assignment percentages between SSR and SNP markers were also reported by independent studies in various maize germplasms [ 38, 48, 49] and were attributed to the greater information content of SSRs [ 50].
The expression of other tight junction markers were also assessed between peripheral and central regions (Figure 6).
Each bin contained between one and nine markers; nine markers were also shared with other chromosomes.
Strong associations between the relative abundance of bacterial taxa and inflammatory markers were also found.
Myogenic markers were also negative.
Linkage disequilibrium between functional markers was also calculated using the same software.
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