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When m = 2, the proposed sharpness metric used the correspondence blocks of the two highest-sharpness candidate blocks (i = 1,2), and a similar pattern was used for other values of m. Figure 8a shows the average LCC plots of Datasets I and II as a function of the number of blocks for candidate-block sizes of 50, 75, 100, and 125 pixels.
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The loading plots of all datasets displayed a similar influence of the genes to the first two PCs: the group of genes containing IL8, TREM1, SERPINE1, BIRC3, and TNFAIP3 were separated from the group containing VEGF, ADM, ZNF395, and KISS1R in the 2nd PC (Fig. 2A).
Plots of empirical datasets relating the response of a group of exposed individuals to the dose (often expressed as a logarithm) frequently show a sigmoid shape, and can be fitted by a large number of mathematical functions.
Scatter plots are displayed in the main window of Galaxy's analysis interface, making it possible to do visual analysis by toggling between running analysis tools and generating plots of output datasets.
Kaplan-Meier plots of 12 datasets showed that the 11823860_ST2 gene set classified patients into two groups (poor or good prognosis) according to differences in survival or recurrence in eight of 12 datasets.
Box plot representations, frequency distribution plots, and scatter plots of the dataset are provided to enrich its value.
When highlighting the differentially expressed genes from our re-analysis of the Higgins et al. dataset on the volcano plot of our dataset, we observe a similar apparent bifurcation of our observations into a group of genes that show very little change and another group of genes that is more highly changed.
Instead of comparing the scree plots of newly generated datasets with that of the original one, we used the distribution of percentages explained by the first two components in random datasets to assess the significance of components extracted in the original dataset.
The FDR threshold for the identification of differentially expressed genes has been set at 0.01. Figure 1 shows the q- values plots of the six datasets analyzed.
Overall, the spatial harbor arrangement was coherent between the MDS plots of the whole datasets and those of introduced species and, to a lesser degree, between abundance and presence absence data (Fig. 4).
TWINSPAN classification was applied on selected plots of a plant dataset to distinguish vegetation types and identify the indicator species of each different type.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com