![]() The Operation section describes how to call the endpoint as a Cytoscape Automation Function. In this paper, the Implementation section describes the general approach of aMatReader and its REST endpoints. Researchers can then utilize Cytoscape’s filtering tools to remove redundant or unremarkable edges between components, slimming the network and emphasizing stronger relationships to further their analysis. With Cytoscape Automation, biologists can manipulate Cytoscape networks via REST calls and create complex workflows in their language of choice (e.g. aMatReader aims to enable users to compile Cytoscape networks from one or multiple matrix files by creating edges or edge attributes for nonzero values in the matrix.Ĥ, bridging the gap between network matrix data in automation scripts and Cytoscape. Many analysis tools deal with networks in the form of an adjacency matrix, and exposing the aMatReader API to automation users enables scripts to transfer those networks directly into Cytoscape with little effort.Īdjacency matrices are a strong choice for storing pairwise element interaction data, such as those commonly produced by biological analysis tools to represent a weighted network of relationships between biological components (such as genes, conditions, pathways, times, etc.).ĪMatReader facilitates importing general adjacency matrices (such as correlation, similarity, and difference data) into edge attributes of Cytoscape networks. We also exposed CyREST endpoints to allow researchers to import network matrix data directly into Cytoscape from their language of choice. To accelerate the import process, aMatReader attempts to predict matrix import parameters by analyzing the first two lines of the file. Our goal was to import the diverse adjacency matrix formats produced by existing scripts and libraries written in R, MATLAB, and Python, and facilitate importing that data into Cytoscape. TheĪMatReader app enables users to import one or multiple adjacency matrix files into Cytoscape, where each file represents an edge attribute in a network. Adjacency matrices are useful for storing pairwise interaction data, such as correlations between gene pairs in a pathway or similarities between genes and conditions. ![]()
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