Copy number variation profile of prostate cancer dataset was downloaded from The Cancer Genome Atlas (TCGA; https://gdc.cancer.gov/ ). The analysis method for copy number variation profile was as following: download the Level 3 Copy Number Variation (CNV) dataset of prostate cancer in SNP6.0 microarray from TCGA; analyze the dataset by GISTIC2.0 software as described previously (all parameters as the default) [34 (link)]; procure the CNV number of each corresponding sample and define the CNV number of Amplification and Gain groups as “Gain” and the rest as “No Gain”; analyze the result using Excel 2010 and depict each figure using GraphPad 5 software.
Graphpad5
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GraphPad5 software is a data analysis and graphing tool for scientific research. It provides a range of statistical analysis functions and options for creating high-quality graphs and visualizations from experimental data.
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Lab products found in correlation
Spss statistic, by IBM (2 mentions)
Origin 6, by Malvern Panalytical (1 mentions)
Dapi d9542, by Merck Group (1 mentions)
Image pro plus software, by GraphPad (1 mentions)
Spss statistical package v 17, by IBM (1 mentions)
Spss 19, by IBM (1 mentions)
Mts assay, by Promega (1 mentions)
Jmp 12, by SAS Institute (1 mentions)
Lightcycler 480 system, by Roche (1 mentions)
Statistical package for the social sciences version 18, by IBM (1 mentions)
30 protocols using graphpad5
1
Prostate Cancer Copy Number Variation
2
Comparative Statistical Analysis of Experimental Data
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The data are expressed as the mean ± standard deviation and are illustrated using GraphPad 5 software (GraphPad Software, Inc., San Diego CA, USA). The SPSS 17.0.1 (SPSS Inc., Chicago, IL, USA) software was used for the statistical analysis. The data were assessed by ANOVA or a Student's t-test. p < 0.05 was considered statistically significant.
3
Electrophysiological Analysis of Ion Channel Function
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Data points in graphs are presented as the mean ± standard error of the mean for the number of experiments as shown in individual figures. Current-voltage and current-time relationships were plotted using either Graph Pad 5 software (San Diego, California) or Origin 6.0 Software (Microcal Software Inc., Northampton, MA, USA). Statistical significance was determined either by unpaired Student’s t-test, one-way or two-way ANOVA as appropriate; significance level set at P< 0.05, followed by Bonferroni post-hoc tests as appropriate. Boltzmann analysis was performed using GraphPad Prism, version 6.05 (San Diego, California) and the equation G/Gmax = 1/(1+exp((V50-Vm/slope)). Conductance, G, for each membrane potential (Vm) was calculated using an equilibrium potential for K+ of -80 mV from the equation G = I/Vm-EK. Gmax was defined as the average maximal conductance for each experimental group. Values are given with 95% confidence intervals.
4
Comparative Analysis of qPCR and ddPCR
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The qPCR versus ddPCR comparison was performed on log transformed data. qPCR results were calculated based on the standard curve (adjusted for MFC infiltration at diagnosis), while ddPCR results were expressed as amount of target copies per 105 cells, considering that 75.000 cells correspond to 500 ng of gDNA (∼6.6 pg/cell; ie, 1 copy of target or one positive droplet/replicate in 500ng corresponds to 1.3E-5). All BQL and negative samples were imputed arbitrarily at 1E-6 and 1E-8 respectively, for graphical representation, as done for qPCR results within Euro-MRD.23 (link)To calculate the correlation and agreement between the methods, we evaluated the test-retest reliability for continuous variables by a single-measurement, consistent, 2-way mixed-effects model, Inter Class Correlation (ICC) analysis, with a 95% confident interval (CI).14 (link) The strength of agreement of MRD positivity versus negativity between the two methods was calculated using the Cohen's k coefficient for categorical variables (graphpad.com/quickcalcs) (rather than continuous variables, as assessed by ICC analysis), thus also allowing inclusion of BQR and BQL results.14 (link) Correlation analyses and their representation plots were performed using IBM SPSS Statistics (version 25.0. Armonk, NY: IBM Corp.) or GraphPad5 Software (GraphPad Software Inc, San Diego, CA).
5
5hmC Enrichment Quantitative RT-PCR
6
Oyster Hemocyte Phagocytosis Kinetics
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Oyster hemocytes were cultured in confocal dishes with a suspension at a density of 105 cells/mL and a volume of 500 µL per sample. After 15 min of incubation, cells were infected for 15 min, 30 min, and 60 min by adding pH-sensitive BioParticles (P35361, Thermo Fisher, USA) at a concentration of 1 mg/mL. Cells were then washed three times to remove extracellular particles. After phagocytosis, paraformaldehyde (4%, cold) was used to terminate the phagocytic process and fix cells for 15 min. Cells were washed three times with PBS, followed by DAPI (D9542, Sigma, USA) staining of nuclei for 5 min. For each time point, several pairs of images (generally four) were acquired with appropriate filters by Leica LP8X confocal microscopy. After acquisition, images were analyzed by Image Pro Plus software and corresponding fluorescence intensity data by GraphPad5 software.
7
One-way ANOVA Analysis of Experimental Data
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Statistical analysis was performed using one-way ANOVA (GraphPad 5 Software, Graphpad Software Inc., La Jolla, CA, USA). All data were expressed as mean ± standard deviation. Significance was assumed for P < 0.05. All experiments were carried out in a randomized fashion, with each experiment performed three times from three different culture sets. Investigators analyzing the data did so in a blinded fashion.
8
Comparing Group Means with t-Test
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All statistical analyses were performed using SPSS 19.0 (SPSS, Chicago, IL, USA) and GraphPad5 software. The Student's t-Test was used to determine the statistical difference between means of two groups and data. P < 0.05 were considered as significant.
9
Serum Soluble E-Cadherin Prognostic Potential
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The relationships between clinicopathologic variables and serum soluble E-cad expression were examined by χ2 analyses. The Receiver Operating Characteristic (ROC) curve was used for the prediction of cut-off values of the markers. Survival curves were calculated using the Kaplan-Meier method and compared with the log-rank test. Factors shown to be of prognostic significance in the univariate Cox regression model were evaluated in a multivariate Cox regression model. For all analyses, a P value less than 0.05 was considered statistically significant. All analyses were performed using SPSS18.0 (SPSS, Chicago, IL) and GraphPad5 software. All statistical tests were 2-sided.
10
EV Analysis in Patient Samples
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Data were analyzed using GraphPad-5 software. Continuous variables were reported as mean ± SD and as median and interquartile range. Differences between controls and patients were tested using Mann–Whitney test; to compare subgroups, Kruskal–Wallis test was performed with subsequent Dunn’s multiple comparison test. To further reduce the risk of false discovery due to multiple testing, the Benjamini–Hochberg false discovery rate method was used to adjust the P-values. Spearman’s correlation test was used to correlate EV results with the patients’ laboratory parameters. For all analyses, two-tailed test with significance P < 0.05 was used.
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