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Testing data distribution was performed using the Kolmogorov-Smirnov test.
Test for normality of data distribution was performed (Kolmogorov-Smirnov test) a priori.
General assessment of the data distribution was performed with Principle Component Analysis, boxplot and log-log data plots.
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Data distribution is performed by DAS servers and is separated from visualization which is performed by DAS clients.
Comparison of continuous data with a skewed distribution was performed using the non- parametric Mann–Whitney U test and categorical data by the Chi-squared test.
A three steps testing of normal distribution was performed for each data set: 1. Graphic display (QQ-plot, histogram and box plot), 2. Ratio analysis, 3. Kolmorogov-Smirnov (with Lilliefors significance correction) and Shapiro-Wilks testing.
Analysis of mitochondrial distribution was performed with support from Leica.
Correlations between data subsets with a normal distribution were performed using Pearson's Correlation Coefficient; non-normally distributed datasets were analyzed for correlation using Kendall's Correlation Coefficient.
The Chi-Squared goodness of fit test, Mann–Whitney U test and exact hypothesis test with binomial distribution were performed to analyse data.
Comparisons of one-variable data following Gaussian distributions were performed using a two-tailed unpaired Student's T-test.
Comparisons between the three groups with respect to the medians of the data exhibiting non-parametric distributions were performed with the Kruskal Wallis test.
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