The inter-rater reliability agreement among the 11 different scorers (9 humans and 2 automated scorers) was assessed using the ICCs for the different respiratory indices. Additionally, we also determined the ICCs of the average of the manual scoring and the two automated systems. The levels of agreement using the ICCs of respiratory indices were classified as follows: 0.00–0.25 = little, 0.26–0.49 = low, 0.50–0.69 = moderate, 0.70–0.89 = strong, and 0.90–1.00 = very strong [17 , 18 (link)]. We also calculated the mean difference (MEANdiff) between the average of the manual scores and the automated scores of the AHI. The limits of agreement (LoA) were calculated as mean difference ± 1.96*SD of the differences [19 (link)]. Data analyses were performed using SPSS software version 23 (IBM Corp., Armonk, NY). The Bland-Altman plots were generated using SigmaPlot software version 13 (Systat Software, Inc., San Jose, CA).
Sigmaplot software version 13
Manufactured by Grafiti LLC
Sourced in United States, Germany
SigmaPlot software version 13.0 is a data analysis and graphing tool used for scientific and engineering applications. It provides functions for data manipulation, statistical analysis, and the creation of high-quality graphs and plots.
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Lab products found in correlation
12 protocols using sigmaplot software version 13
1
Evaluating Automated Respiratory Scoring
2
One-way ANOVA and Dunnett's Test
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One-way analysis of variance followed by Dunnett’s test was used to determine the significance of intergroup differences. Statistical analysis was performed using SigmaPlot software version 13 (Systat Software, San Jose, CA, USA, 2014). p-values of <0.05 were considered to be statistically significant.
3
Visualization and Statistical Analysis
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CorelDraw 2018 (Corel Corporation) was used for figure preparation Statistical analysis was carried out using Sigmaplot software version 13 (Systat Software Inc.) and, for each use, the test parameters are indicated in the figure legends and, where appropriate, in the main text. All graphs present the means as a bar chart and the individual data points are overlaid as discrete dots. All N values quoted refer to distinct biological replicates.
4
Transcriptional Analysis of RNA-seq Data
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The RNA-seq data set in the NCBI Gene Expression Omnibus (GEO) database, accession number GSE118116 , was analyzed to assess transcriptional units and compared to the meta-analysis of GSE18149 , GSE33176 , GSE41014 , and GSE53636 carried out by Peña-Castillo et al. (44 (link)). Transcript abundance was visualized using the Broad Institute’s IGV viewer (95 (link)). Protein alignments were made in ClustalΩ (96 (link)) and then visualized in Jalview (97 (link)). FIJI software (98 (link)) was used to analyze microscopy images. Statistical analysis was carried out using SigmaPlot software version 13 (Systat Software Inc., Slough, UK; www.systatsoftware.com ), and for each use, the test parameters are indicated in the text and/or figure legends. All data presented in figures correspond to one representative experiment consisting of at least three biological replicates; all experimental data were confirmed on at least two different occasions. CorelDraw 2018 (Corel Corporation, Ottawa, Canada) was used for figure preparation and ChemDraw (Perkin Elmer, Waltham, MA, USA) for chemical structure diagrams.
5
Statistical Analysis of Pain and Functional Outcomes
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The statistical analyses were performed using SigmaPlot software version 13.0 (Systat software Inc., San Jose, CA, USA). Normality of the data was tested with the Shapiro-Wilk test. Descriptive data are reported as frequencies, means and standard deviation (SD) or median and interquartile range (IQR). For analyses of group differences in frequencies χ2-test was used. For analyses of group differences of variables on a nominal scale t-test was used, while the Mann–Whitney U-test was used for variables on an ordinal scale. The Friedman’s analysis of variance (ANOVA) on ranks with Dunn’s test as post hoc test was used for analyses of changes between baseline data and follow-up measurements regarding pain variables and emotional functioning, while 2-way repeated measures ANOVA with Holm-Sidak as post hoc test was used for physical functioning and changes in PPT. The Pearson correlation-test with Bonferroni-correction for multiple comparisons was used to correlate the P-5-HT levels with baseline and outcome variables. The significance level was set at P < 0.05.
6
Spore Inactivation Kinetics Assessment
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Spore survival was determined from the quotient N/N0, where N is the average CFU (colony forming units) of treated samples and N0 is the average CFU of untreated controls. The logarithm of N/N0 was plotted as a function of each treatment to obtain survival curves. Spore inactivation was expressed as the lethal dose at which 90% of the spore population is inactivated (LD90) [50 (link)]. Each experiment was performed in triplicate and all data are expressed as averages ± standard deviations. Significant differences in survival rates were calculated by single-factor analysis of variance (ANOVA), using SigmaPlot software Version 13.0 (Systat Software GmbH, Erkrath, Germany). Differences were considered statistically significant at P < 0.05.
7
Statistical Analysis of Myocarditis and DCM
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Data were tested for normal distribution. The results are presented either as mean values ± standard error of the mean in the case of continuous data or as median values with their respective 25th and 75th percentiles in the case of non‐continuous data. All comparisons between groups with unpaired data were performed using Student's t‐test when normal distributed, otherwise with the Mann–Whitney U test. For the FACS analysis, besides comparison of controls with respective myocarditis and DCM data, a further analysis of longitudinal paired data within groups was performed using either the Friedman test (analysis of variance) when at least three data sets were available (i.e. for the three DCM measurements at baseline and follow‐ups 1 and 2), or the Wilcoxon signed‐rank test when less than three data sets were available (i.e. for the two myocarditis measurements at baseline and the single follow‐up). Correlation analyses were performed using the Spearman rank order test. For all tests, a P‐value <0.05 was considered statistically significant. Correlation analysis including correlation graphs were performed with Sigma Plot Software Version 13.0 (Systat Software Inc.) All other statistical analysis and graphs were performed using GraphPad Prism Version 7.03 (GraphPad Software Inc., La Jolla, CA, USA).
8
Inflammatory Mediator Protein Analysis
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Protein levels of inflammatory mediators are represented as median with range. mRNA and microRNA expression data are represented as ΔCt values with mean ± standard deviation (SD). Scatter diagram were plotted using GraphPadPrism softwareversion 7.03. One-way analysis of variance (ANOVA) followed by Dunnett’s test/Tukey’s post-hoc test is used as required to analyze the data between more than two group. A p-value of <0.05 is considered statistically significant. Sigma Plot softwareversion 13.0 (SYSTAT SOFTWARE INC) is used for statistical analyses.
9
Kruskal-Wallis ANOVA and Dunn's Test
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Treatment effects were analyzed by Kruskal-Wallis One Way Analysis of Variance on Ranks and significant differences between treatments and the non-treated control were analyzed using Dunn’s Method (tested at P < 0.05) using the SigmaPlot Software, Version 13.0 (Systat Software, Inc., San Jose California USA).
10
Statistical Analysis of Experimental Data
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Statistical analysis was carried out using SigmaPlot Software version 13.0, build 13.0.0.83 (Systat Software GmbH, Erkrath, Germany). If not otherwise noted, data are presented as means ± SD. The Grubbs’s test was used to remove extreme outliers. Differences between the experimental groups and conditions were tested with a one-way or two-way analysis of variance, accordingly. Post-hoc comparisons were made with the Holm–Sidak test. Differences were considered significant with p < 0.05.
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