Sas software v 8

Manufactured by SAS Institute

Sourced in United States

SAS software v.8.1 is a comprehensive suite of data analysis and statistical software tools. It provides a range of functionalities for data management, statistical modeling, and reporting. The software is designed to handle large and complex data sets, enabling users to extract insights and make informed decisions.

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Origin v8, by OriginLab (1 mentions)

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SAS software (6040 citations) SAS 8.2 (473 citations) SAS software v. 8 for Windows (2 citations)

9 protocols using sas software v 8

Disease Resistance Profiling in RILs

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The average of notes generated from four plants per RIL per block corresponded to the
final disease score of each line. These values were used for analysis of variance and
F tests using the general linear models (GLM) procedure, using SAS software v.8.2
(SAS Institute, Cary, NC, USA). Broad sense heritability (h²) was
estimated according to Falconer and Mackay
(1996). In order to confirm the contrasting resistance profile among
genotypes, separate analyses were performed for the parents and recombinant inbred
lines. Effects of different sources of variation were considered significant by F
test when P ≤ 0.05. Skewness, kurtosis (Mardia,
1970) and Shapiro and Wilk (1965)
normality tests were applied to verify normal distribution of variance analysis
residuals.

Bassi D., Briñez B., Rosa J.S., Oblessuc P.R., de Almeida C.P., Nucci S.M., da Silva L.C., Chiorato A.F., Vianello R.P., Camargo L.E., Blair M.W, & Benchimol-Reis L.L. (2017). Linkage and mapping of quantitative trait loci associated with angular leaf spot and powdery mildew resistance in common beans. Genetics and Molecular Biology, 40(1), 109-122.

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Analyzing Insect Mortality Using GLM

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The generalized linear model (GLM) was used to perform a one-way analysis of variance on the insect mortality data [32 (link)]. Means were then compared by the Duncan’s least significant difference (LSD) test [75 (link)] using SAS software V. 8.2 (SAS Institute Inc., Cary, NC, USA) [76 ]. Differences were considered significant at α = 0.05. The LdP line computerized software program was used to calculate the probit analyses of LC₅₀ values and their fiducial limits (confidence intervals) for botanical oils according to Finney (1971) [77 (link)].

Shawer R., El-Shazly M.M., Khider A.M., Baeshen R.S., Hikal W.M, & Kordy A.M. (2022). Botanical Oils Isolated from Simmondsia chinensis and Rosmarinus officinalis Cultivated in Northern Egypt: Chemical Composition and Insecticidal Activity against Sitophilus oryzae (L.) and Tribolium castaneum (Herbst). Molecules, 27(14), 4383.

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Triplicate Assay Analysis with ANOVA

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All assays were performed in triplicate. The results were analyzed using ANOVA for multiple comparisons followed by the Duncan test using SAS software v.8.1 (SAS institute, Cary, NC, USA), with significance levels of 0.01.

He W.J., Zhang L., Yi S.Y., Tang X.L., Yuan Q.S., Guo M.W., Wu A.B., Qu B., Li H.P, & Liao Y.C. (2017). An aldo-keto reductase is responsible for Fusarium toxin-degrading activity in a soil Sphingomonas strain. Scientific Reports, 7, 9549.

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Statistical Analysis of Experimental Data

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Analysis of variance (ANOVA) and correlation analysis was performed for data obtained from different experiments using PROC GLM and PROC CORR, respectively, in SAS Software v.8.1 (SAS Institute, 2000 ). Broad-sense heritability (h²) was calculated from variance components according to Kearsey and Pooni (1996) . Data obtained from the imaging platform was analysed using R Software (R Development Core Team, 2013 ). Non-linear models were fitted with the nls function of the R package.

Parent B., Shahinnia F., Maphosa L., Berger B., Rabie H., Chalmers K., Kovalchuk A., Langridge P, & Fleury D. (2015). Combining field performance with controlled environment plant imaging to identify the genetic control of growth and transpiration underlying yield response to water-deficit stress in wheat. Journal of Experimental Botany, 66(18), 5481-5492.

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Statistical Analysis of Experimental Data

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All the results were analyzed using ANOVA for multiple comparisons followed by the Duncan test using SAS software v.8.1 (SAS institute, Cary, NC, USA), using significance levels of 0.01.

He W.J., Yuan Q.S., Zhang Y.B., Guo M.W., Gong A.D., Zhang J.B., Wu A.B., Huang T., Qu B., Li H.P, & Liao Y.C. (2016). Aerobic De-Epoxydation of Trichothecene Mycotoxins by a Soil Bacterial Consortium Isolated Using In Situ Soil Enrichment. Toxins, 8(10), 277.

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Statistical Analysis of Experimental Data

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The data were subjected to one-factor analysis of variance (ANOVA) in the SAS software (v 8.1), significant differences between the treatments was compared by the Duncan’s multiple range test at the level of 0.05. Pearson’s correlation coefficients (r) between variables were tested by the CORR procedure in the SAS software.

Li Q.S., Xie Y.C., Rahman M.M., Hashem A., Abd_Allah E.F, & Wu Q.S. (2022). Arbuscular Mycorrhizal Fungi and Endophytic Fungi Activate Leaf Antioxidant Defense System of Lane Late Navel Orange. Journal of Fungi, 8(3), 282.

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Statistical Analysis of Experimental Data

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Results were evaluated with analysis of variance (ANOVA) for multiple comparisons followed by Duncan’s new multiple range test using SAS software v.8.1 (SAS institute, Cary, NC, USA), using significance levels of 0.05.

He W.J., Shi M.M., Yang P., Huang T., Yuan Q.S., Yi S.Y., Wu A.B., Li H.P., Gao C.B., Zhang J.B, & Liao Y.C. (2020). Novel Soil Bacterium Strain Desulfitobacterium sp. PGC-3-9 Detoxifies Trichothecene Mycotoxins in Wheat via De-Epoxidation under Aerobic and Anaerobic Conditions. Toxins, 12(6), 363.

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Triplicate Analyses Using Statistical Tools

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All trials were carried out in triplicate. Microsoft Excel 2020(Microsoft Co., Redmond, WA, USA) was used to create tables, and Origin v8.0 (OriginLab, Northampton, MA, USA) and Microsoft PowerPoint 2016(Microsoft Co., Redmond, WA, USA) were used to create figures. SAS software v8 was used to analyze variance and regression (SAS Institute Inc., Carry, NC, USA). Duncan’s multiple range test was used to determine differences between mean values. Significant differences were confirmed when p < 0.05.

Ma C., Liu D., Hao H, & Wu X. (2022). Identification of the DPP-IV Inhibitory Peptides from Donkey Blood and Regulatory Effect on the Gut Microbiota of Type 2 Diabetic Mice. Foods, 11(14), 2148.

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Statistical Analysis of Gene Expression in RCC

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All statistical analyses were performed using SAS software v8. The significance of differences between cancer and normal tissues was estimated by Paired Student’s t-test. κ 2 test was performed to test the relationship between gene expression and clinical parameters. Correlation between expression levels of VHL and Jade-1 genes in RCC tissues was analyzed using Spearman’s linear correlation. Two-sided P-values were calculated, and a probability level of 0.05 was chosen for statistical significance.

Xiao-fen W., Ting C., Jie L., Deng-yang M., Qing-feng Z, & Xin L. (2016). Correlation analysis of VHL and Jade-1 gene expression in human renal cell carcinoma. Open Medicine, 11(1), 226-230.

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