Spss statistical package

Hierarchical cluster analysis of significantly differentially expressed transcripts was performed using the function heatmap.2 of gplots in R (v 3.0.2) and the optimal number of clusters were obtained by generating a scree diagram plotting the distance against the cluster numbers. K-means clustering method using 100 iteration in SPSS statistical package (v 12.0) was further applied to partition transcripts according to their expression pattern. The number of centers was determined by the plot of the within groups sum of squares by number of clusters. Corroboration of the cluster assignments was assessed using canonical discriminant analysis. Principal component analysis (PCA) with maximal iteration 25 was computed with the SPSS statistical package (v 12.0) as well as with the prcomp function using the default parameters in R (v 3.0.2). In brief, Eigenvalues greater than 1 were extracted, thus the first three principal components form the extracted solution were kept for further analysis accounting for almost 50 % of the variability. To assure suitability of PCA analysis, Kaiser-Meyer-Olkin measurements as well as Barletts Test of Sphericity were performed. The first three components were visualized by a 3D plot in R (v 3.0.2).

The Mann–Whitney U-test was used to compare the expression level of miRNA-29c, and SPSS statistical package (version 16.0, Chicago, IL, USA) to evaluate the association between the expression level of miRNA-29c and different clinical features. Then, a multivariate model was developed to adjust the most important covariates, including gender, age, drinking, smoking and hypertension. SPSS statistical package (version 16.0, Chicago, IL) was used for all statistical analysis. P < 0.05 indicated a significant difference.

The SPSS statistical package (Version 25.0; IBM SPSS Inc., Chicago, Illinois, USA) and the Microsoft Excel Software were applied for the statistical analysis. The one-way repetitive measurement and analysis of variance was applied to analyze the difference of spherical equivalent (SE), astigmatism, uncorrected distant visual acuity (UDVA), SR, MTF cutoff, OSI and wavefront aberrations before surgery and at 1, 6 and 12 months after surgery when the data followed the law of normal distribution. Otherwise, the Friedman test was used. The paired t-test was used to analyze the difference of age, SE, astigmatism, UDVA, SR, MTF cutoff, OSI and wavefront aberrations at each point of time between the two groups. And the multiple-factor repetitive measurement and analysis of variance was used to compare the pre and post-operative variation of SE, astigmatism, UDVA, SR, MTF cutoff, OSI and wavefront aberrations between the SMILE and FS-LASIK group. p < 0.05 was taken as being statistically significant, and the adjusted alpha i.e., alpha/no. of test, was adopted for the analysis with repeated measurement.