R software v4

Manufactured by R Project for Statistical Computing

Sourced in United States, Austria

R is a free and open-source software environment for statistical computing and graphics. R version 4.0.3, released in October 2020, is the latest stable version. The core function of R is to provide a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, etc.) and graphical techniques, and is highly extensible.

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Lab products found in correlation

Prism 8, by GraphPad (5 mentions) Prism v9, by GraphPad (3 mentions) Spss version 23, by IBM (3 mentions) Spss v26, by IBM (2 mentions) Prism v7, by GraphPad (2 mentions) Spss v21, by IBM (2 mentions) Sas v9, by SAS Institute (2 mentions) Spss 24, by IBM (2 mentions) Spider v 1, by R Project for Statistical Computing (1 mentions) Spss statistics for windows version 26, by IBM (1 mentions) Stata mp v17, by StataCorp (1 mentions) Medcalc v 15, by MedCalc (1 mentions) Spss v19, by IBM (1 mentions) Spss software version 25, by IBM (1 mentions) 200 nm polystyrene beads, by NanoFCM (1 mentions) Monodisperse silica beads, by NanoFCM (1 mentions) Flow nanoanalyzer, by NanoFCM (1 mentions) Spss statistics v28, by IBM (1 mentions) Spss software v24, by IBM (1 mentions) Spss v22, by IBM (1 mentions)

Close spelling variants of this product

R software (3634 citations) R software version v4.0.3 (14 citations) R software (v4.0; (5 citations) R Statistical Software (v4.2.2; (3 citations) V4.0.3 R software (2 citations) R Project software (v4.1.1; (2 citations)

154 protocols using r software v4

DNA Barcoding of Biomphalaria Specimens

Cited 4 times

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In order to verify the accuracy of the partial coi sequences for the identification of Biomphalaria specimens using DNA barcoding methodology, BOLD Identification Criteria (thresh-ID) and Best Close Match (BCM) analyses were carried out (Meier et al., 2006 (link)) using the ape v. 5.5 (Paradis and Schliep, 2019 (link)) and spider v. 1.5.0 (Brown et al., 2012 (link)) packages of the R software v. 4.0.5 (R Foundation for Statistical Computing, 2021 ).
In order to define the barcode gap, the Kimura two-parameter (K2P) model (Tamura et al., 2004 (link)) was used to calculate the intraspecific and interspecific distances (Meyer and Paulay, 2005 (link)) between the species using the spider v. 1.5.0 (Brown et al., 2012 (link)) package in the R software v. 4.0.5 (R Foundation for Statistical Computing, 2021 ).
Additionally, the sequences were clustered/grouped into Operational Taxonomic Units (OTUs), grouping organisms by their similarity, in this case in relation to a genetic marker (Blaxter et al., 2005 (link)), using the criteria of four algorithms; Generalized Mixed Yule-Coalescent (GMYC) (Reid and Carstens, 2012 (link); Fujisawa and Barraclough, 2013 (link)), Poisson Tree Processes (bPTP) (Zhang et al., 2013 (link)), Automatic Barcode Gap Discovery (ABGD) (Puillandre et al., 2012 (link)) and Assemble Species by Automatic Partitioning (ASAP) (Puillandre et al., 2021 (link)).

de Araújo A.D., Carvalho O.D., Gava S.G, & Caldeira R.L. (2023). DNA barcoding as a valuable tool for delimiting mollusk species of the genus Biomphalaria Preston, 1910 (Gastropoda: Planorbidae). Frontiers in Cellular and Infection Microbiology, 13, 1167787.

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Preoperative Irradiation Impact on Survival

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The power analysis (power = 80%, α = 0.05) from our pilot study (unpublished) on three cases with preoperative irradiation and five without in five HPFs, revealed that the minimum number of subjects is 58. Data was presented by the median lower and upper quartiles. Mann-Whitney U test was used for comparing of the study groups. ROC analysis was used to evaluate the threshold criterion, including area under the curve (AUC). A relative risk (RR) analysis was performed using Fisher two-tail test. According to the threshold criteria, the log-rank test and multivariate Cox proportional hazards regression analyses were employed for Rad⁺ group to determine differences in DFS and hazard ratio (HR). Next, correlations between groups of cases were assessed using a Spearman correlation test. All data analyses and visualization were performed using GraphPad Prism v.8.4.3 (GraphPad Software Inc., San Diego, CA, USA) and R Software v4.0.5 (R Foundation for Statistical Computing, Vienna, Austria) and packages dplyr 1.0.5, corrplot 0.89 and Hmisc 4.5-0.

Zinovkin D.A., Lyzikova Y.A., Nadyrov E.A., Petrenyov D.R., Yuzugulen J, & Pranjol M.Z. (2021). Gamma-ray irradiation modulates PGRMC1 expression and the number of CD56+ and FoxP3+ cells in the tumor microenvironment of endometrial endometrioid adenocarcinoma. Radiation Oncology Journal, 39(4), 324-333.

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Angiogenesis Factors in Clinicopathology

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R software v4.0.5 (The R Foundation for Statistical Computing, Vienna, Austria) was employed for data analyses. Unless specified, statistical significance was defined at p < 0.05. Cardinality testing was done to evaluate the correlation of clinicopathological characteristics with various groups. The associations between angiogenesis and all factors were explored by univariate and multifactorial Cox analyses. Data were visualized using the R package “ggplot2.”

Shan L., Lu Y., Xiang C.C., Zhu X., Zuo E.D, & Cheng X. (2022). Identification of Five m6A-Related lncRNA Genes as Prognostic Markers for Endometrial Cancer Based on TCGA Database. Journal of Immunology Research, 2022, 2547029.

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Time-dependent Survival Analysis Protocol

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The time-dependent ROC analysis was performed using R software v 4.0.5 (R Foundation for Statistical Computing, Vienna, Austria [19 ]). The time-dependent ROC analysis had used to diagnosis 5-year survival in this study. Other statistical analyses were performed using IBM SPSS Statistics version 26 for Windows (Chicago, IL, USA). Medians and ranges were calculated, and differences were identified using Student’s t test. The Mann–Whitney U test was used for non-parametric analyses. Differences between each category were identified using the Chi-square test or Fisher’s exact test, and the Kruskal–Wallis test was used to identify the differences in continuous variables. Survival curves were produced using the Kaplan–Meier survival method and log-rank test. Hazard ratios (HRs) were calculated, and univariate and multivariate analyses were performed using Cox proportional hazards regression models. The threshold for significance was set up at p < 0.05.

Haneda R., Hiramatsu Y., Kawata S., Honke J., Soneda W., Matsumoto T., Morita Y., Kikuchi H., Kamiya K, & Takeuchi H. (2021). Survival impact of perioperative changes in prognostic nutritional index levels after esophagectomy. Esophagus, 19(2), 250-259.

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Epidemiological Analysis of PCR Positivity

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Statistical analyses were performed using R software v. 4.0.5 (R Foundation for Statistical Computing, Vienna, Austria). The prevalence and its 95% confidence interval (CI), overall and differentiated by different epidemiological data, were calculated, and the existence of a statistical association between PCR positivity rates and explanatory variables (sex, age, breed, lifestyle, habitat, and ecoregion) was evaluated by Fisher’s exact test. P-values less than 0.05 were considered statistically significant.

Panait L.C., Ionică A.M., Cazan C.D., Coroian M., Diacu A.M., Boncea A.M., Mateescu C, & Mihalca A.D. (2023). Apicomplexan haemoparasites in domestic cats in Romania. Parasites & Vectors, 16, 56.

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Ordinal Data Analysis of Pruritus, Hair Loss, and Scales in Patients

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Statistical associations between ordinal data, such as days 0, 14 and 30 and the scores used to assess pruritus, hair loss and the presence of scales and lice, were assessed using the non-parametric Wilcoxon signed-rank test. A P value < 0.05 was considered to be statistically significant. Data were analyzed using R software v. 4.0.5 (R Foundation for Statistical Computing, Vienna, Austria).

Mihalca A.D., Deak G., Panait L.C., Rabei Ș, & Beugnet F. (2022). Efficacy of afoxolaner (NexGard®) against natural infestations with Trichodectes canis in dogs under field conditions. Parasites & Vectors, 15, 317.

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Risk Factors for Diabetes in Tuberculosis

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Frequency distributions and percentages were calculated for all the study variables. The Student’s t-test for the normally distributed variables or Mann-Whitney test was used to compare continuous variables, and the χ² test was used to compare categorical variables. The age-standardised prevalence rate (per 100 000) of patients with TB-DM was calculated using the Korean standard population in 2015. Logistic regression analyses were performed to assess the risk factors for DM among patients with TB. All p values were two-tailed, and a p value of <0.05 was deemed statistically significant. All statistical analyses were performed using Stata/MP V.17 (StataCorp, College Station, Texas, USA), and R software (V.4.0.5, The R Foundation for Statistical Computing, Vienna, Austria).

Jeong D., Mok J., Jeon D., Kang H.Y., Kim H.J., Kim H.S., Seo J.M., Choi H, & Kang Y.A. (2023). Prevalence and associated factors of diabetes mellitus among patients with tuberculosis in South Korea from 2011 to 2018: a nationwide cohort study. BMJ Open, 13(3), e069642.

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Evaluating Pruritus, Hair Loss, and Lice

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Statistical analyses were performed separately for the group tested with NexGard Combo^® and the reference positive control group. Statistical associations between categorical variables, such as days 0, 14 and 30 and the scores used to assess pruritus, hair loss and the presence of scales and lice, were evaluated using the non-parametric Wilcoxon signed-rank test. Results were considered statistically significant at a p-value < 0.05. Data analyses were performed using R software v. 4.0.5 (R Foundation for Statistical Computing, Vienna, Austria).

Mihalca A.D., Deak G., Panait L.C., Rabei Ș, & Beugnet F. (2022). Efficacy of a topical formulation containing esafoxolaner, eprinomectin and praziquantel (NexGard Combo®) against natural infestations with the cat louse, Felicola subrostratus under field conditions. Parasite, 29, 62.

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Statistical Analysis of Clinical Data

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The study populations’ characteristics were described using summary statistics. We made no assumptions about missing data and expressed proportions with regard to the number of patients with data. Categorical variables were described as the frequency (percentage), and continuous variables were described as the mean (standard deviation) or the median (interquartile range), depending on the data distribution. Intergroup differences were assessed using the Wilcoxon rank sum test or the Kruskal–Wallis test for continuous variables and the chi-squared test or Fisher’s exact test for categorical variables. Kaplan-Meier survival curves were plotted using the survival package in R. All tests were two-sided and a p value < 0.05 was considered significant. All statistical analyses were performed using R software v. 4.0.2 R Foundation for Statistical Computing, Vienna, Austria.

Geiss R., Sebaste L., Valter R., Poisson J., Mebarki S., Conti C., Vordos D., Bringuier M., Méjean A., Mongiat-Artus P., Cudennec T., Canoui-Poitrine F., Caillet P, & Paillaud E. (2021). Complications and Discharge after Radical Cystectomy for Older Patients with Muscle-Invasive Bladder Cancer: The ELCAPA-27 Cohort Study. Cancers, 13(23), 6010.

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Lipidomic Statistical Analysis Methods

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The lipidomic results were statistically analyzed with LINT-web[14 (link)]. Other statistical analysis was performed via R software V.4.0.2 (R Foundation for Statistical Computing, http://www.r-project.org/, accessed date: 10 October 2022) and GraphPad Prism 8.0 (GraphPad Software, San Diego, CA, USA). Two-tailed Student’s t-test, Kolmogorov−Smirnov test and Wilcoxon test was used for the indicated comparisons. p < 0.05 was considered statistically significant (* p < 0.05, ** p < 0.01, *** p < 0.001, ns, no significance).

Song Z., Wang S., Lu L., Xu J., Zhou Q., Lu W., Tong H., Zhang Y., Liu W., Wang Z., Li W., You Y., Zhang C., Guo X., Luo R., Hou Y., Wang C., Wang Y., Sun L., Huang H, & Zhou Y. (2022). Lipidomics and Transcriptomics Differ Liposarcoma Differentiation Characteristics That Can Be Altered by Pentose Phosphate Pathway Intervention. Metabolites, 12(12), 1227.

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