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The Kolmogorov-Smirnov test and an analysis of variance (ANOVA) test with the Bonferroni correction were used to investigate significant differences between different sample groups.
To analyze the differences in focal adhesion number between different sample groups, images were collected and processed.
The autocorrelation terms arise from the interference occurring between different sample reflectors within the target.
The centrifugal force significantly enhanced both metallurgical alloying and mechanical interlocking between different sample layers during product formation.
Then using a series of pairwise comparisons between different sample sets we calculated fold change and p values (Student's t-test).
Groups generated from hierarchical clustering were then compared between different sample through the similarity analyses based on three miRNAs expression conditions, highly expressed (normalized expression value lower than 0), expressed (normalized expression value greater than 0) or not expressed.
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The MAE performance difference between different sampling rates is reduced as SNR decreases.
Global differences between different samples were measured by Principal Component Analysis (PCA) and Linear Discrimination Analysis (LDA).
Therefore, RPKM values were directly used to compare gene expression differences between different samples.
The dramatic differences between different samples suggest strongly that gene activities alter dramatically between different developmental stages of male reproductive organs [ 33].
The statistical significance of differences between different samples was assessed by one-way ANOVA with pairwise comparisons or by student t-test.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com