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Prism 8 and 9

Manufactured by GraphPad
Sourced in United States

GraphPad Prism 8 and 9 are data analysis and graph plotting software designed for scientific and medical researchers. The software enables users to analyze, visualize, and present their data through a variety of statistical and graphical tools.

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14 protocols using prism 8 and 9

1

Statistical Analysis Methods for Research

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Statistical details of experiments can be found in the figure legends and exact p values are indicated in the figures when P > 0.0001. Mean, median, standard deviation (SD), and standard error of the mean (SE) were determined using the built-in functions in Matlab (MathWorks, R2018a) or Prism 8 and 9, (GraphPad, version 8.4.1; version 9.0.1). Two-tailed Wilcoxon matched-pairs signed rank test and two-tailed Mann–Whitney test were performed using Prism 8 and 9 (GraphPad) software.
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2

Statistical Analysis Methods in Research

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Statistical analyses were performed using R v4.1.0 or GraphPad Prism 8 and 9 as indicated in the legends and Methods. No statistical methods were used to predetermine sample sizes, but our sample sizes are similar to those reported in previous publications27 (link),66 (link). Data distribution was assumed to be normal, but this was not formally tested.
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3

Zebrafish Cartilage Degeneration Analysis

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Experimental and control zebrafish for each experiment were age- and stage-matched using standard body length (Parichy et al., 2009 (link)). Two independent researchers performed blinded OARSI scoring on 3–5 representative toluidine blue-stained images for each scored joint for all experiments (as per Askary et al., 2016 (link)). The OARSI scores for zebrafish joints were compared by ANOVA and Tukey’s multiple-comparison test (Figure 1) and Kruskal–Wallis ANOVA test with Dunn’s multiple-comparisons test (Figure 3) to determine significance between groups using GraphPad Prism 8 and 9. The Sox10+ cell counts in adult joint cartilage were assessed by two-tailed Student’s t-test in GraphPad Prism 8 and graphically represented as individual counts, mean, and standard error of the mean for each condition. The Sox10+/PCNA+ cell counts in jaw joint articular cells were quantified as a proportion of total Hoescht-stained nuclei by researchers blinded to the treatment. Percentages of Sox10+/PCNA+ nuclei were analyzed with Welch’s t-test in GraphPad Prism 9, graphically represented as individual counts, mean, and standard error of the mean for each condition.
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4

Mogamulizumab Efficacy Analysis

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The relationships between groups were compared using a t-test or the nonparametric Mann–Whitney U test. For multiple group comparisons, the Dunnett test was employed. PFS and OS were defined as the time from the initial mogamulizumab administration until the first observation of disease progression and death from any cause, respectively. PFS and OS were investigated with the Kaplan–Meier method and were compared among the groups using the log-rank test or Cox regression proportional hazards analysis. Statistical analysis was performed with GraphPad Prism8 and 9 (GraphPad Software, San Diego, CA) or R version 3.1.1 (R Foundation for Statistical Computing, Vienna, Austria). P values less than 0.05 were considered significant.
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5

Single-cell RNA Profiling of Natural Killer Cells

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Statistical analysis was performed using GraphPad Prism 8 and 9 (GraphPad Software, Inc., La Jolla, CA) or R (R 4.0.3 GUI 1.73; R Studio, Version 1.3.1093, lme4, ggplot2, FactoMineR and factoextra packages). Principal component analysis was generated with R using the mRNA expression of 52 genes of 440 single CD56bright ihNK cells or pbNK cells. Wilcoxon matched-pairs signed rank test was used to determine differences between paired samples with assumed non-normal distribution. To assess normal distribution within small sample sizes, the Shapiro-Wilk test was applied and subsequently, the paired t test was used. A mixed-effects model with random intercept, considering intra-sample correlations, was used to compare the single-cell mRNA expression data from different donors (or groups). To limit the detection of false positives, the p-values were adjusted by the Benjamini and Hochberg False Discovery Rate (FDR) method between each comparison groups (cutoff of 0.05). P values <0.05 were considered statistically significant. Statistical analysis for additional data presented in the figures are provided in the respective figure legends.
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6

Statistical Analysis of Experimental Data

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Data are presented as the mean ± SEM. Statistical analysis was performed using GraphPad Prism 8 and 9 (GraphPad Software). An unpaired t test with Welch’s correction was used to compare differences between 2 groups. Multiple-group comparisons were performed using one- or two-way ANOVA with Tukey’s multiple comparison test. Differences were considered statistically significant when a P value was less than 0.05.
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7

Comparative Analysis of Treatments

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Data are presented as the mean ± SEM. Statistical analysis was performed using GraphPad Prism 8 and 9 (GraphPad Software). An unpaired t test was used to compare differences between 2 groups. Multiple-group comparisons were performed using one- or two-way ANOVA with the Holm-Sidak multiple comparison test. Differences were considered statistically significant when a P value was less than 0.05.
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8

Statistical Analysis of Experimental Data

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Statistical analysis was performed with one-way ANOVA with Tukey’s multiple comparisons test using GraphPad Prism 8 and 9 (GraphPad Software).p values of 0.05 or lower were considered to denote significance. All values are means and SEMs, unless otherwise specified. The sample numbers (n) are indicated in figure legends.
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9

Statistical Analysis of Experimental Data

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Graphs and statistical analysis were performed using Microsoft Excel and GraphPad Prism 8 and 9 software. Data groups were compared via a one-way ANOVA. Tukey’s and Dunnet’s test were used for the statistical hypothesis testing, and the family-wise alpha threshold and confidence level was set at 0.05 (95% confidence level). The P values of the data sets are provided in the Source data.
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10

Statistical Analysis of Non-Parametric Data

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All statistical tests were performed using Prism 8 and 9 (GraphPad, Boston, USA). For non‐parametric unpaired or paired datasets, the Mann–Whitney U‐test or the Wilcoxon test were used for comparisons respectively. Spearman's rank‐order correlation was used to analyse the correlation for non‐parametric data. Correlation matrixes were generated in R using the Hmisc and corrplot packages. Non‐numerical data were grouped and analysed using Fisher's exact test. The significance levels were defined as *P < 0.05, **P < 0.01, ***P < 0.001 and ****P < 0.0001.
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