R language

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R is a programming language and software environment for statistical computing and graphics. It provides a wide variety of statistical and graphical techniques, and is highly extensible. R is widely used in academic and research settings for data analysis, visualization, and statistical modeling.

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Lab products found in correlation

Spss version 25, by IBM (1 mentions) Spss statistic, by IBM (1 mentions) Prism software, by GraphPad (1 mentions)

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R programming language (5 citations) R language software (3 citations) R language 4.0.5 (2 citations) R statistical language v4 (2 citations)

9 protocols using r language

Statistical Analysis of Research Data

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SPSS version 25.0 (IBM, Armonk, NY, USA) was used for the statistical analysis. For measurement data, we first performed a normality test. If the data were normally distributed, measurement data were expressed by using means and standard deviations (SDs); if the data were not normally distributed, then the measurement data were expressed by the median and interquartile range; for categorical data, rates or composition ratios were used. R language (Vienna, Austria) was used to deal with missing values, using the Mice package (Multiple Imputation).
The SEM of SPSS version 25.0 (IBM, Armonk, NY, USA) was used for path analysis. The parameters of the model were estimated by the maximum likelihood method. First, the initial path model was adjusted based on two criteria. One was to delete insignificant paths, and the other was to use the modification index to establish the correlation between some residuals using the combination of professional knowledge to gain the best model.

Shen B., Chen H., Yang D., Yolanda O., Yuan C., Du A., Xu R., Geng Y., Chen X., Li H, & Xu G.Y. (2021). A Structural Equation Model of Health-Related Quality of Life in Chinese Patients With Rheumatoid Arthritis. Frontiers in Psychiatry, 12, 716996.

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Statistical Analysis of Morphological Features

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The statistical analysis was executed by using IBM SPSS Statistics (version 22.0 Inc., Chicago, IL, USA) and the R language (version 3.6.3, Vienna, Austria). Continuous variables were represented as mean with standard deviation and categorical variables were summarized by way of count and percentage. The odds ratio (OR) and 95% confidence interval (CI) were figured. To avoid potential multicollinearity, the Kendall rank correlation analysis was performed between the LD and the SD of RLN LN since both of these were the morphological features of nodes. A P-value <0.05 was regarded as statistically significant.

Chen T.T., Yan H.J., He X., Fu S.Y., Zhang S.X., Yang W., Zuo Y.J., Tang H.T., Yang J.J., Liu P.Z., Wen H.Y, & Tian D. (2022). A novel web-based dynamic nomogram for recurrent laryngeal nerve lymph node metastasis in esophageal squamous cell carcinoma. Frontiers in Surgery, 9, 898705.

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Multimodal MRI Biomarkers in Multiple Sclerosis

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The data were analyzed using SPSS (version 17.0, IBM, USA) and R language (version 3.6.1).¹ The two-sample t-test and the Chi-squared test were used to compare the ages and genders of MS and HCs. We used the intraclass correlation coefficient (ICC) to analyze the consistency of MTRaysm (3.5 ppm), FA, and ADC values measured by two neuroradiologists, with the ICC = 0.89, 0.82, and 0.85, respectively, regarded excellent consistency (ICC ≥ 0.75, excellent; 0.60 ≤ ICC < 0.75, good; 0.40 ≤ ICC < 0.60, fair; and ICC < 0.40, poor) (Shieh, 2016 (link)). Using receiver operating characteristic (ROC) plot, the area under the curve (AUC) was utilized to evaluate the performance of MTRaysm (3.5 ppm), FA and ADC values in differing the brain lesions of MS patients. Pearson’s correlation analysis was used to analyze the correlations between MTRaysm (3.5 ppm), FA and ADC values and EDSS, MSSS, T25WT, 9-HPT, SDMT scores, disease durations, and sNfL of the MS patients. P < 0.05 was considered statistically significant.

Huang J., Liang Y., Shan Y., Zhao C., Li Q., Shen Z., Dong H., Qi Z, & Lu J. (2023). Altered amide proton transfer weighted and diffusion signals in patients with multiple sclerosis: correlation with neurofilament light chain and disease duration. Frontiers in Neuroscience, 17, 1137176.

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Sputum CST1 Diagnostic Biomarker for Asthma

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R language (version 4.0.3), SPSS software (version 25), and GraphPad software (version 8.3.0) were used for all statistical analyses. For normally distributed data, we calculated means ± standard deviation (SD) and used Student’s t-test to compare across the groups. For non-normally distributed data, we calculated medians with interquartile ranges and used non-parametric tests (Mann-Whitney test) to compare across the groups. We analyzed the correlation using Spearman's rank-order correlation. The χ² test was used for categorical measures. Receiver operator characteristic (ROC) curve analysis and Youden’s index were used to determine the optimal cutoffs for sputum CST1 level in diagnosing asthma. A P value of < 0.05 was considered statistically significant.

Du L., Xu C., Tang K., Shi J., Tang L., Lisha X., Lei C., Liu H., Liang Y, & Guo Y. (2023). Epithelial CST1 Promotes Airway Eosinophilic Inflammation in Asthma via the AKT Signaling Pathway. Allergy, Asthma & Immunology Research, 15(3), 374-394.

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Statistical Analysis of Experimental Data

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R language (v3.6.3), SPSS software (v22.0), and GraphPad Prism (v8.0) for Windows were used for statistical analyses and generating figures. All error bars in graphical data represent the mean ± SE. Spearman's rank correlation was used to analyze the association. The Student's two-tailed t-test and the Wilcoxon test were used to determine the statistical relevance between groups, and p < 0.05 was considered significant.

Zi H., Tuo Z., He Q., Meng J., Hu Y., Li Y, & Yang K. (2022). Comprehensive Bioinformatics Analysis of Gasdermin Family of Glioma. Computational Intelligence and Neuroscience, 2022, 9046507.

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Integrative Omics Analysis of Biological System

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Results were presented as frequency and percentage for categorical variables, mean ± standard deviation
(SD) for normally distributed continuous variables and median (interquartile range) for not normally distributed continuous variables. Data analysis and statistical plotting were performed using R language (version 4.1.1), SPSS software (version 26.0), and GraphPad Prism software (version 9.0). The normality of each data group was assessed using the One Sample Kolmogorov-Smirnov test. For comparisons between two independent samples, either the t-test or Wilcoxon rank sum test was employed. Differences among multiple groups were assessed using one-way ANOVA or the Kruskal-Wallis test. Categorical variables were compared using the chi-square test. Two-way orthogonal partial least squares (O2PLS) analysis was performed to integrate transcriptomic and metabolomic data. Spearman’s correlation analysis was applied to assess the correlation between variables. P-value <0.05 was considered statistically significant.

Zhang L., Zheng Z., Huang H., Fu Y., Chen T., Liu C., Yi Q., Lin C., Zeng Y., Ou Q, & Zeng Y. (2024). Multi-omics reveals deoxycholic acid modulates bile acid metabolism via the gut microbiota to antagonize carbon tetrachloride-induced chronic liver injury. Gut Microbes, 16(1), 2323236.

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TERT Mutation Impact on Survival

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R language (v. 3.6.2), SPSS software (v. 22.0), and GraphPad Prism (v. 8.3.0) for Windows were used for statistical analyses and generating figures. Two-tailed Student’s t-test was used to separate the genes with differential expression according to TERT mutation. Correction of p-values was performed to control the false discovery rate (FDR) using R-values of FDR < 0.01, which were considered statistically significant. The multivariate Cox proportional hazard model was used to evaluate independent prognostic variables, and Kaplan–Meier curves were employed to depict survival distributions. Immune cells that correlated with the TERT mutation status were explored by a two-tailed Student’s t-test using SPSS, considering the effect of variant grades or IDH status.

Gao M., Lin Y., Liu X., Zhao Z., Zhu Z., Zhang H., Ban Y., Bie Y., He X., Sun X, & Zhang S. (2021). TERT Mutation Is Accompanied by Neutrophil Infiltration and Contributes to Poor Survival in Isocitrate Dehydrogenase Wild-Type Glioma. Frontiers in Cell and Developmental Biology, 9, 654407.

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Comparative Clinicopathological Characteristics

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Student’s t-test or the chi-squared test were performed to clarify the differences in clinicopathological characteristics among these samples. p < 0.05 was considered statistically significant. correlation analysis of various factors and graphic work were accomplished by R language (Version 4.0.2) and SPSS (SPSS Inc., Chicago, Ill., USA).

Ma W., Zhang K., Bao Z., Jiang T, & Zhang Y. (2021). SAMD9 Is Relating With M2 Macrophage and Remarkable Malignancy Characters in Low-Grade Glioma. Frontiers in Immunology, 12, 659659.

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Prognostic Impact of Tumor Deposits

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Before PSM, baseline information was compared between the TD-negative and TD-positive groups. The χ2 test or Fisher test was used to compare the categorical variables. The Mann Whitney U test was used to compare the ordered categorical variables. 5-OS rates were calculated for each group using the Kaplan-Meier method. The log-rank test was used to compare survival differences between groups. COX regression models were used for univariate and multivariate analysis of prognostic factors. To reduce selection bias and differences in baseline information, a 1:1 PSM analysis was performed between the TD-positive and TD-negative groups. A dichotomous logistic regression model was used to assess the propensity score, and the matched variables were age, gender, tumor location, histological differentiation, tumor size, pT stage, lymphovascular invasion, perineural invasion, and type of gastrectomy. Based on this propensity score, patients in TD-positive group were matched with patients in TD-negative group by the nearest neighbor method, with the caliper set to 0.2. SPSS24.0 Chicago IL and R language version3.4.2 was used for all statistical analyses, and P < 0.05 was considered statistically significant.

Xu R., Zhang Y., Zhao J., Chen K, & Wang Z. (2023). Prognostic value of tumor deposits in lymph node-negative gastric cancer: A propensity score matching study. European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology, 49(4).

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