Table 2 Visualization tools available in PreP+07
From: PreP+07: improvements of a user friendly tool to preprocess and analyse microarray data
Name | Method | Use |
|---|---|---|
Slide view | A synthetic reproduction of the scanned image from the available data. | Comparison with the scanned image, identifying single spots, splitting the slide in blocks and manual testing. |
Slide view of coherent spots | A synthetic reproduction of the scanned image only for coherent data. | Evaluation of the quality of the slide and poorly scanned zones (negative or null values are not shown). |
Slide view with quality | Uses the blue channel for displaying the quality of the measure. | Combined with algorithms that provide a quality value for each spot. |
AM and RG Graphs | (AM) Logarithmic plot of ratio versus intensity; or (RG) log. of red versus green channel | AM displays the dependencies of the ratio on the intensity (ratio correction and filtering); in the (RG) case the two color channels are emphasizing separately. |
Box Graph | Box graph of each block of the slide. | Classical statistical graph for detecting outliers and comparing the distribution of diverse data sets (useful tool for detecting contrast variations inter- or intra-slide). |
Density Graph and Density Graph per block | This graph estimates the density of ratios (per block). | Preliminary test on the distribution of the ratios. The expected density graph is a normal distribution (per block, helps detecting spatial errors). |
Intensity-Intensity Graph | A scatter plot showing the intensity values of one scan acquisition versus the same values of another scan acquisition. | This is a first step for comparing two slides. The data should be near the diagonal if the slides are good replicates of each other. |
Dispersion, Deviation and Correlation of Replicates | The intensity values of the individual spots versus the mean of all the spots from the same replication group. | Quality estimation of the replication. For dispersion graph, the data points should be along the diagonal, and the more noise, the more blurred they will be. If the deviation is high the quality will decrease |
Normality of Replications | Applies the inverse of the normal distribution function to the distribution function of each replication group. | One typical assumption is that the noise is normally distributed. This graph will test that hypothesis. If the data points lie along the diagonal, the noise is normal. |
Probability Normal Plots (PP/QQ/PN) | Plots to compare expected normal distribution values against observed values | QQ compares z-scores, PP p-values and PN compares pvalues vs logratios |