R software version 3

Manufactured by GraphPad

R software version 3.6.0 is a free and open-source programming language and software environment for statistical computing and graphics. It is widely used for data analysis, visualization, and statistical modeling.

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Lab products found in correlation

Prism 8, by GraphPad (2 mentions) Prism version 7, by GraphPad (1 mentions) Prism version 8, by GraphPad (1 mentions) Prism 7, by GraphPad (1 mentions) Spss ver 22, by IBM (1 mentions)

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R software (53 citations) R version 3.6.1 (36 citations) R software 3.6.3 (8 citations) R software (version 3.6.3), (3 citations)

6 protocols using r software version 3

Statistical Analysis of Experimental Data

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Data were checked for normality and similar variances between groups
and Student’s t-tests were used when appropriate. Mann-Whitney U
tests were used to compare data between two groups when the data did not
follow a normal distribution. The Kaplan-Meier curves were used to depict
survival probabilities and the log-rank test was applied to compare survival
curves. For clinical data analysis, non-repeated ANOVA was used to compare
continuous variables, while chi-square or Fisher’s exact tests were
used to analyze the frequency distribution between categorical variables.
Analyses were performed using R software version 3.6.0 and Prism version 7.0
(GraphPad Software, San Diego, CA). P values < 0.05 were considered
statistically significant.

Hayase E., Hayase T., Jamal M.A., Miyama T., Chang C.C., Ortega M.R., Ahmed S.S., Karmouch J.L., Sanchez C.A., Brown A.N., El-Himri R.K., Flores I.I., McDaniel L.K., Pham D., Halsey T., Frenk A.C., Chapa V.A., Heckel B.E., Jin Y., Tsai W.B., Prasad R., Tan L., Veillon L., Ajami N.J., Wargo J.A., Galloway-Peña J., Shelburne S., Chemaly R.F., Davey L., Glowacki R.W., Liu C., Rondon G., Alousi A.M., Molldrem J.J., Champlin R.E., Shpall E.J., Valdivia R.H., Martens E.C., Lorenzi P.L, & Jenq R.R. (2022). Mucus-degrading Bacteroides link carbapenems to aggravated graft-versushost disease. Cell, 185(20), 3705-3719.e14.

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Serum Cerium and Oral Cancer Risk

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Chi-square tests or Fisher's exact tests were used to compare the distribution of demographic characteristics and environmental factors. The difference of serum Ce between cases and controls was assessed by the Wilcoxon rank-sum test and shown by violin charts. Associations between serum Ce and oral cancer were assessed by calculating odds ratios (ORs) and 95% confidence intervals (95%CIs) using unconditional logistic regression models. Moreover, stratified analyses and interaction terms were used to test the potential modification effects of environmental factors on the level of serum Ce for oral cancer. Additionally, the method proposed by Katsouyanni et al. (15 (link)) was utilized to develop a prediction model for oral cancer risk. The predictive ability of the models was evaluated using area under the receiver operating characteristic (ROC) curve (AUC). All tests were based on a 2-sided P < 0.05 as evidence of statistical significance. Data analysis was performed using R software version 3.6.0 or GraphPad prism8.0.

He B., Wang J., Lin J., Chen J., Zhuang Z., Hong Y., Yan L., Lin L., Shi B., Qiu Y., Pan L., Zheng X., Liu F, & Chen F. (2021). Association Between Rare Earth Element Cerium and the Risk of Oral Cancer: A Case-Control Study in Southeast China. Frontiers in Public Health, 9, 647120.

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Prognostic Signature for Survival Analysis

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In this study, the R software version 3.6.2 and the GraphPad Prism version 8.0 were used. Univariate and multivariate Cox regression analyses were performed by R package “survival”, at the same time, Harrell’s concordance index (C-index) was calculated to assess the performance of the model. The ggforest plots were generated by R package “survminer”. Kaplan-Meier algorithm was used to evaluate the survival time of high/low-risk groups, and a Log-rank test was employed. To test the predictive ability of the prognostic signature, the area under the curves (AUC) of receiver operating characteristic (ROC) was calculated and plot by R package “pROC”. The random forest algorithm was carried out by R package “randomForest”. The Lasso regression analysis was implemented by R package “glmnet”. The Spearman Correlation Coefficient was calculated by R method “cor.test ()”, and the correlation heatmaps were plotted by GraphPad Prism 8.0. The Mann-Whitney U test was used to compare the xCell score of cells in different groups. All statistical tests were two-sided and a p-value < 0.05 was considered statistically significant.

Zhong X., Tao Y., Chang J., Zhang Y., Zhang H., Wang L, & Liu Y. (2021). Prognostic Signature of Immune Genes and Immune-Related LncRNAs in Neuroblastoma: A Study Based on GEO and TARGET Datasets. Frontiers in Oncology, 11, 631546.

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Pontine Lesions Differentiate MS from VRF

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Agreement was measured as previously reported.^{4 (link)} The number of infratentorial lesions and the proportion of cases with peripheral and central pontine lesions were compared between MS without VRF, MS with VRF, and non-MS with VRF. Variables are presented as median and interquartile range (IQR). Chi-square or Fisher’s exact test and nonparametric tests were applied as appropriate. Considering potential differences between MAGNIMS sites, a ‘site’ factorial variable was built. Comparisons between MS without VRF and non-MS with VRF regarding the presence of central and peripheral pons lesions, adjusting for age and site, were made using a generalized linear model with methods for bias reduction and maximum penalized likelihood; results are presented as odds ratios (exponential coefficients EXP(B)) and 95% confidence intervals (CI). A p value < 0.05 was considered statistically significant. The specificity (number of true negative cases/number of false positive cases + true negative cases) of peripheral pontine lesions for MS and of central pontine lesions for VRF-SVD was assessed by comparing MS without VRF and non-MS with VRF cases. Specificity and 95% CI were calculated using MEDCALC statistical software. All other analyses were performed with SPSS version 25, R software version 3.6.2, and GraphPad Prism version 7.

Geraldes R., Juryńczyk M., dos Passos G.R., Pichler A., Chung K., Hagens M., Ruggieri S., Auger C., Sastre-Garriga J., Enzinger C., Chard D., Barkhof F., Gasperini C., Rovira A., DeLuca G, & Palace J. (2020). The role of pontine lesion location in differentiating multiple sclerosis from vascular risk factor-related small vessel disease. Multiple Sclerosis (Houndmills, Basingstoke, England), 27(6), 968-972.

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Genetic Association Analysis Protocol

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Statistical analysis was managed using the R software version 3.3.2, GraphPad prism 7.0, and "Statistical Package for the Social Sciences (SPSS) for Windows" software, version 23. Online software, (http://www.oege.org/software/hwe-mr-calc.shtml) was used for calculating Hardy–Weinberg equilibrium. Chi-square, Fisher's exact, Student's t-, Mann-Whitney U (MW), and Kruskal-Wallis (KW) tests were used. Genotype and allele frequencies were estimated for each group to calculate the odds ratios (ORs) and 95% confidence intervals (CIs) for multiple genetic association models.26 (link) Logistic regression was employed to adjust confounder parameters. A two-tailed p P < 0.05 was considered statistically significant.

Sahmoud S., Ibrahim M.S., Toraih E.A., Kamel N., Fawzy M.S, & Elfiky S. (2020). Association of VDBP rs4701 Variant, but not VDR/RXR-α Over-Expression with Bone Mineral Density in Pediatric Well-Chelated β-Thalassemia Patients. Mediterranean Journal of Hematology and Infectious Diseases, 12(1), e2020037.

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Comprehensive Analysis of Molecular Markers

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R software version 3.3.2, GraphPad prism 7, PC-ORD ver. 5, and SPSS ver. 22 were employed for analysis and presentation. Data profiling was tested for outliers and no Log transformation was performed. Two-way agglomerative hierarchical clustering was executed for data exploration. Chi-square (χ 2 ) and Fisher's exact tests were used for comparison. Correlation analysis by Spearman's rank test was done. A two-tailed P < 0.05 was considered statistically significant. The area under the curve (AUC) of receiver operating characteristic (ROC) was plotted to the quantified markers (LINC-ROR, caspase 3, and p53). The Kaplan-Meier curve was performed for survival analysis, and Log rank, Breslow, and Tarone-Ware tests were used for factor comparison.

Toraih E.A., El-Wazir A., Hussein M.H., Khashana M.S., Matter A., Fawzy M.S, & Hosny S. (2019). Expression of long intergenic non-coding RNA, regulator of reprogramming, and its prognostic value in patients with glioblastoma. The International journal of biological markers, 34(1).

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