Sigmaplot 11

Manufactured by Merck Group

Sourced in United States, Italy, Germany

SigmaPlot 11.0 is a data analysis and graphing software developed by Systat Software Inc. It is designed to create high-quality scientific graphs and perform advanced data analysis. The core function of SigmaPlot 11.0 is to provide users with tools for data visualization, curve fitting, and statistical analysis.

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Lab products found in correlation

Prism 5, by GraphPad (13 mentions) Prism 7, by GraphPad (7 mentions) Prism 8, by GraphPad (5 mentions) Stata 13, by StataCorp (4 mentions) Sigmastat 3, by Merck Group (4 mentions) Prism 9, by GraphPad (3 mentions) Prism 6, by GraphPad (3 mentions) Originpro 8, by OriginLab (2 mentions) Prism 6, by Merck Group (2 mentions) Openoffice 4, by Merck Group (2 mentions) Prism 6.0c, by GraphPad (2 mentions) Sigmaplot v11, by Merck Group (1 mentions) Gradpad prism, by GraphPad (1 mentions) Multi gauge v3, by Fujifilm (1 mentions) Statistica 13, by StatSoft (1 mentions) Statistical product and service solutions software, by IBM (1 mentions) Lsm 710 confocal microscope system, by Zeiss (1 mentions) Centurion xvi, by Statgraphics (1 mentions) Sigmaplot, by Merck Group (1 mentions) Stata 10, by StataCorp (1 mentions)

Close spelling variants of this product

SigmaPlot (794 citations) SigmaPlot version 11.0 (39 citations) SigmaPlot 11.0 for Windows (15 citations) SigmaPlot for Windows Version 11.0 (12 citations) SigmaPlot ver. 11 (7 citations) SigmaPlot software (v.11.0) (2 citations) SigmaPlot 11 for Windows 7 (1 citations)

564 protocols using sigmaplot 11

Quantification of extracellular matrix in cell culture

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GAG and HYPRO data are expressed as mean ±SD. The effect of culture time and transfection were analyzed by 2-way ANOVA using Tukey’s t-test for post hoc analysis performed in SigmaPlot 11 (SYSTAT, Chicago, IL), with significance determined with p<0.05. The temporal patterns in GAG and HYPRO data were then fit to equation 5 using SigmaPlot 11, which calculated best fit values of [ECM]_SS and τ, with the uncertainties in these fits expressed as standard error.
Each steady state values and standard errors were normalized to alginate (0 μM) steady state value for GAG and HYPRO. The normalized values were fitted to Equation 6 using software SigmaPlot 11, which enabled the calculation of best fit values for EC₅₀, [ECM]_max, and [ECM]_min values and their uncertainty, expressed as standard error. Statistical differences between EC₅₀, [ECM]_max, and [ECM]_min were determined by an unpaired t test using GradPad Prism (GraphPad, Inc., La Jolla, CA).

Aguilar N.I., Trippel S., Shi S, & Bonassar L.J. (2017). CUSTOMIZED BIOMATERIALS TO AUGMENT CHONDROCYTE GENE THERAPY. Acta biomaterialia, 53, 260-267.

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Dose-Response Curve Analysis

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Statistical analyses were performed using SigmaPlot 11.0 software and methods described in the figure legends. Bar and symbol representation, along with error bars, are described in figure legends. Unless otherwise noted, scatter plots represent the average of three independent experiments measured in triplicate. For bar charts, the bars represent the average of three independent experiments, whereas the overlaid points report the values from the individual experiments measured in triplicate. All errors are reported as standard deviation. The responses to the CXCL12 titration experiments were fit to sigmoidal dose-response model using SigmaPlot 11.0 and statistical significance was determined using the extra sum-of squares F test. One-way ANOVA follow by Bonferroni t-test was used to determine statistical significance and P values for all other comparisons using SigmaPlot 11.0.

Schafer C.T., Chen Q., Tesmer J.J, & Handel T.M. (2023). Atypical Chemokine Receptor 3 ‘Senses’ CXC Chemokine Receptor 4 Activation Through GPCR Kinase Phosphorylation. bioRxiv.

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Statistical Analyses for Biological Experiments

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Statistical analyses were performed using SigmaPlot 11.0 software and methods described in the figure legends. Bar and symbol representation, along with error bars, are described in figure legends. Unless otherwise noted, scatter plots represent the average of three independent experiments measured in triplicate. For bar charts, the bars represent the average of three independent experiments, whereas the overlaid points report the values from the individual experiments measured in triplicate. All errors are reported as standard deviations. The responses to the CXCL12 titration experiments were fit to a sigmoidal dose–response model using SigmaPlot 11.0, and statistical significance was determined using the extra-sum-of-squares F test. One-way analysis of variance (ANOVA) followed by a Bonferroni t test, or unpaired t test in the case of comparing two samples, was used to determine statistical significance and P values for all other comparisons using SigmaPlot 11.0.

Schafer C.T., Chen Q., Tesmer J.J, & Handel T.M. (2023). Atypical Chemokine Receptor 3 “Senses” CXC Chemokine Receptor 4 Activation Through GPCR Kinase Phosphorylation. Molecular Pharmacology, 104(4), 174-186.

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Comparative Statistical Analysis Methods

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All data are given as means ± SEM. Statistical significance was determined by one-way ANOVA in combination with the Holm-Sidak posthoc test by using SigmaPlot 11 software (Systat). Normality of data was tested using SigmaPlot 11 software. If this test failed, ANOVA on ranks was used (see figure legends). For statistical comparison of no more than two experimental groups Student’s t-test was performed by using SigmaPlot 11 software.

van Stegen B., Dagar S, & Gottmann K. (2017). Release activity-dependent control of vesicle endocytosis by the synaptic adhesion molecule N-cadherin. Scientific Reports, 7, 40865.

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Quantifying Fluorescence Changes in Biological Samples

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Change in fluorescence (ΔF/F) was calculated by (F_t–F₀)/F₀, where F_t is measured fluorescence (in arbitrary units, a.u.) at a given time t and F₀ is initial baseline fluorescence, typically calculated from averaging the 10 first images. ΔF/F = 1 describes an increase by 100%, equivalent to twofold increase in fluorescence. Owing to easily observable basal fluorescence (see Supplementary Figures 4e–g for multiple examples), we did not need encounter near division-by-zero artifacts. For collecting emission spectra, we used small imaging intervals (8 nm, see above) which allowed us to plot the data as smooth (splined) curves rather than straight lines (SigmaPlot 11). We find no differences between the two plots (e.g., Supplementary Figure 5e). All results are displayed as mean ± SEM. Sample sizes are provided (summarized in Table 1). Significance was tested using one-way ANOVA (post hoc Tukey) where relevant and relationship between Ca²⁺-performance and extent of photoactivation was tested by Spearman correlation using SigmaPlot 11.

Hussein W, & Berlin S. (2020). Red Photoactivatable Genetic Optical-Indicators. Frontiers in Cellular Neuroscience, 14, 113.

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Statistical Analyses for Genotype and Sex

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SigmaPlot 11 was used for analyses (Pairwise Multiple Comparison Procedures [Holm-Sidak method]; 2-way ANOVA; RMANOVA, as appropriate) within a treatment, across genotype, and across sex. Details are provided in the figure legends. For all comparisons with statistically significant differences, alpha=0.05, and data are expressed as mean ± SEM. Calculations of η2 were performed according to http://www.uccs.edu/lbecker/glm_effectsize.html using the SigmaPlot11 output.

Mandela P., Yan Y., LaRese T., Eipper B.A, & Mains R.E. (2014). Elimination of Kalrn Expression in POMC Cells Reduces Anxiety-Like Behavior and Contextual Fear Learning. Hormones and behavior, 66(2), 430-438.

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In vivo Electrophysiology of Dorsal Horn Neurons

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In vivo electrophysiological data were analyzed offline using CED Spike2 version 8 software and imported to SigmaPlot 11 or GraphPad Prism 5 for statistics. Data were extracted from Spike2 to SigmaPlot 11 at a rate of 100 Hz for DHN unit firing rate, average whole RSNA, and mean arterial pressure (MAP). Spike2 software was used to extract single DHN units from evoked bursts of ensemble DHN activity based on template matching and principal component analysis, allowing identification of one to four WDR DHN units for each recording site (Fig. 1C). Baseline values for evoked firing frequency of DHNs, which were altered by dPAG microinjections, ranged from 0.5 to 14.5 Hz with a mean of 3.0 and a median of 2.3 Hz. To eliminate noise from RSNA, zero activity was obtained at the end of the experiment by crushing the nerve proximal to the recording electrodes, averaging the remaining noise level, and subtracting it from the averaged activity.

Roberts C.J., Hopp F.A., Hogan Q.H, & Dean C. (2022). Anandamide in the dorsal periaqueductal gray inhibits sensory input without a correlation to sympathoexcitation. Neurobiology of Pain, 12, 100104.

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Biochemical Pathway Optimization Protocol

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All statistical comparisons were made by ANOVA, with normality of values tested by the Shapiro-Wilk test followed by a multiple comparison of means test with the Holm-Sidak method as performed through SigmaPlot 11. In general, the number of replications was five for each value, with a minimum of two replicate experiments. All EC50 and IC50 values were generated with the curve-fitting procedure provided by the four-parameter logistic analysis with in SigmaPlot 11.

Brenneman D.E., Petkanas D, & Kinney W.A. (2018). Pharmacological Comparisons between Cannabidiol and KLS-13019. Journal of molecular neuroscience : MN, 66(1), 121-134.

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Statistical Analyses for Measurement Uncertainties

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Nonparametric statistical analyses were employed (Hsu, 2013 (link)), including (1) Mann–Whitney rank sum test (Sigmaplot 11, San Jose, CA); (2) Spearman rank order correlation (Sigmaplot 11); (3) Mann–Kendall trend analysis (XLSTAT-Time, Addinsoft, New York, NY); and (4) Sen trend analysis (XLSTAT-Time). In addition, two regression analyses were applied: (1) simple linear regression analysis (SLR, Excel 2013, Redmond, WA) to assess the association between the independent and dependent variables without consideration of measurement uncertainties; and (2) orthogonal regression (OR; Minitab 16, State College, PA), which recognizes measurement uncertainties in both variables (Hauck et al., 2004 (link)). Pearson correlation coefficients (Excel 2013, Redmond, WA) and Spearman rank order correlation coefficients were calculated for the SLR and OR analyses, respectively.

Hsu Y.M., Wang X., Chow J.C., Watson J.G, & Percy K.E. (2016). Collocated comparisons of continuous and filter-based PM2.5 measurements at Fort McMurray, Alberta, Canada. Journal of the Air & Waste Management Association (1995), 66(3), 329-339.

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Apoptosis and HIV-1 Activation Correlation

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Values represent the mean ± SD of at least three independent experiments. Correlation between apoptosis and HIV-1 activation was calculated by performing the Spearman rank correlation test using SigmaPlot 11.0. Data curve fitting (Gompertz) and non-linear regression statistical analyses were accomplished using SigmaPlot 11.0 software.

Khan S.Z., Hand N, & Zeichner S.L. (2015). Apoptosis-induced activation of HIV-1 in latently infected cell lines. Retrovirology, 12, 42.

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