6/20/2023 0 Comments Networkview key![]() ![]() By default, samples are represented by dark grey nodes with sample labels displayed at all zoom levels. The default network layout is Force Spring. Inclusion of large numbers of low activity features can create ‘hairball’ networks that obscure the biologically relevant MS features. Consequently, the network view is most valuable when limited to MS features with strong Activity and Cluster Scores. molecular networking) that group nodes based on chemical similarity, communities in the NP Analyst network view are formed between samples that share MS features above the defined Activity and Cluster Score cutoffs. These networks form communities based on the presence of shared biologically active MS features. The network view contains nodes for both samples and bioactive MS features, connected by edges denoting presence of a given MS feature in a given sample. In the scatter plot these sets of features appear as vertical stripes of features, and can be a useful marker for identifying compounds of interest for further evaluation. In addition, each of them should possess similar Activity and Cluster Scores, given that they all derive from the same molecule. Each of these different features will possess a different m/z value, but the same retention time. +, +), different charge states (2 +), and in-source fragments ( +). These features derive from different adducts (e.g. Often, molecules in sample sets generate more than one MS feature in the metabolomics data. These two filtration methods can be used together to (for example) highlight strongly bioactive features from a specific subset of samples in the sample set. This will remove all MS features in the plot that are not present in the selected samples. If specific samples from the sample set are of particular interest then these samples can be selected and the include/exclude slider set to ‘include’. background contaminants or primary metabolites).Īlternatively, data can be filtered to include or exclude specific samples using the check box list to the right below the scatter plot. Alternatively, reducing the Maximum Feature Count slider removes features that are present with high frequency in the dataset (e.g. For example, increasing the Minimum Cluster Score value removes MS features with inconsistent biological profiles. Below the plot on the left are a set of sliders and data entry boxes that allow users to dynamically modify cutoffs for key values. Data Filtrationĭata in the scatter plot can be filtered in two ways. ![]() The diameter of each node indicates its relative Activity Score (larger nodes = higher Activity Scores). The color scheme of the nodes indicates their Cluster Score values (blue = negative, red = positive). The scatter plot displays bioactive MS features in a plot of retention time (x-axis) vs. Data Visualization Scatter Plot View Overview ![]()
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