![]() ![]() The first two columns must contain metabolite names or ids. The first row of the column-based file must have column headings of the user’s choosing. The first data file format is column-based this is the recommended format. Two types of data file formats are accepted. This portion of the tutorial will cover the data file formats for building a correlation network in MetScape. To learn more about the correlation network in MetScape, please refer to Chapter 6. You can click View in MetScape to view the correlation network in MetScape, where interactive visualization and exploration can be performed. You can click the View CSV File and/or Save buttons to perform these functions. The Correlation Calculator calculates the partial correlation values, p-values, and q-values for each compound pair. I will select Debiased Sparse Partial Correlation, or DSPC, and then click Run. The last step is to use a Partial Correlation Method, either Debiased Sparse Partial Correlation or Basic Partial Correlation. The slider and text fields can be used to filter metabolites to those with correlation coefficients within a specified range. The View CSV File and Save buttons can be used to perform these functions. You can click View Heatmap to view the results as a heatmap. You can click View Histogram to view a histogram of the maximum Pearson’s Correlation by metabolite. To use Pearson’s Correlations, click Run under Calculate Pearson’s Correlations. Now, I will use Pearson’s Correlations to filter out metabolites this step is optional. ![]() If the data are already normalized before loading it into the calculator, this normalization step can be skipped. Click View Normalized Data to view the results. Next, under Data Normalization, select Log2-Transform Data and Autoscale Data. This data file includes labeled samples in rows, so I will make sure that Samples Labeled is checked and Samples in Rows is selected. Select the appropriate data file and click Open. Samples may be in rows or columns.Īfter launching the calculator, click the Browse button. Although metabolites must be labeled, sample labels are optional. The input data file is a CSV file that contains a table of measurements across multiple samples. The Correlation Calculator can be downloaded from the MetScape website. This chapter will cover the Correlation Calculator. The workflow allows inspection and/or saving of results at various stages, and the final correlation results can be dynamically imported into version 3.1 or higher of MetScape as a correlation network. It is designed for use with quantitative metabolite measurements, such as Mass Spectrometry data, on a set of samples. The Correlation Calculator is a standalone Java application that provides methods of calculating pairwise correlations among repeatedly measured entities. This is a one-time, free registration.Ĭorrelations are measures between pairs of metabolites. The first time you open MetScape, a registration page will appear. Once the app is successfully installed, it will appear in the Apps Menu. Click on MetScape and then click on “Install” at the bottom of the window. MetScape should now appear in the second column. First, open Cytoscape and go to the Apps Menu. For this tutorial, I will use the App Manager in the Cytoscape software. To install the MetScape app, you can find MetScape on the Cytoscape App Store webpage and click the Install button, or use the App Manager directly in the Cytoscape software. ![]() ![]() For this tutorial, I will be using Cytoscape version 3.2.1 and MetScape version 3.1.1. For those compounds that do not map to a pathway, correlation-based networks are useful. Currently, between 40% and 60% of experimentally measured compounds can be mapped to canonical metabolic pathways when using untargeted assays. This tutorial will focus on the correlation calculator and correlation networks. This image shows you the various workflows included in this app. MetScape uses data from the Edinburgh Human Metabolic Network and KEGG Compound Database. Although not covered in this tutorial, you can also use this app to view pathway-based networks. It can be used to visualize compound networks and display related information about reactions, enzymes, and pathways. MetScape can be used to visualize and interpret metabolomics and expression profiling data in the context of human metabolic networks. Today, we learn about building correlation networks using MetScape, a Cytoscape app. NARRATOR: Hello, my name is Marci Brandenburg, and I am the Bioinformationist at the University of Michigan Taubman Health Sciences Library. ![]()
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