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Significant differences were analyzed with t-test and one-way ANOVA (followed by a Tukey test) for comparison of two means or multiple comparisons, respectively.
Statistical analysis was performed using ANOVA with post-hoc test for simple and multiple comparisons, respectively.
Continuous variables were analyzed by Mann-Whitney U-test or Kruskal-Wallis test for pairwise or multiple comparisons, respectively.
For parametric analyses of tumor volume reduction, Student's unpaired t-test and the Tukey-Kramer method were performed for two-factor comparisons and multiple comparisons, respectively.
All tests were two-sided and p < 0.05 and p < 0.02 were considered to be significant for single and multiple comparisons respectively.
When significant (P ≤ 0.05) treatment effects were detected, differences between treatment means were determined by Student's t-test or Tukey's test for pairwise and multiple comparisons, respectively.
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Comparisons between two or among groups were made using unpaired nonparametric Student's t-test and ANOVA followed by a Tukey's HSD post hoc multiple comparison respectively.
The parametric data were compared with a one-way ANOVA, and nonparametric data were compared with a Kruskal-Wallis, followed in each case by a post hoc test (Student-Newman-Keuls or Dunn multiple comparison, respectively).
Statistical analysis was performed using the lumi package (Mann-Whitney and Kruskal-Wallis tests for two- and multiple-group comparisons, respectively, adjusting P-values with the FDR algorithm).
The median/mean IC50 values among virus clades were analyzed by using the Kruskal-Wallis 1-way analysis of variance and the Dunn's multiple comparison test, respectively.
Differences in various parameters between control and NPSLE or among various groups of NPSLE were analyzed by the Mann-Whitney U-test or the Kruskal-Wallis test with the Dunn multiple comparison test, respectively, using GraphPad Prism 6 for Mac OS X ver. 6.0b, GraphPad Software, Inc., San Diego, CA, USA.
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multiple modes respectively
multiple conditions respectively
multiple alignments respectively
multiple domains respectively
multiple mismatches respectively
multiple hosts respectively
multiple antennas respectively
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multiple disabilities respectively
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multiple results respectively
multiple births respectively
multiple integrations respectively
multiple subgroups respectively
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