Identifier Mapping in Cytoscape: idmapper [version 1; referees: 1 approved, 2 approved with reservations]

F1000Research 2018, 7:725 Last updated: 19 JAN 2024 SOFTWARE TOOL ARTICLE Identifier Mapping in Cytoscape: idmapper [version 1; peer review: 1 approved, 2 approved with reservations] Adam Treister , Alexander R. Pico Institute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, CA, 94158, USA v1 First published: 11 Jun 2018, 7:725 https://doi.org/10.12688/f1000research.14807.1 Open Peer Review Latest published: 06 Aug 2018, 7:725 https://doi.org/10.12688/f1000research.14807.2 Approval Status 1 Abstract Identifier Mapping, the association of terms across disparate taxonomies and databases, is a common hurdle in bioinformatics workflows. The idmapper app for Cytoscape simplifies identifier mapping for genes and proteins in the context of common biological networks. This app provides a unified interface to different identifier resources accessible through a right-click on the table's column header. It also provides an OSGi programming interface via Cytoscape Commands and CyREST that can be utilized for identifier mapping in scripts and other Cytoscape apps, and supports integrated Swagger documentation. Keywords Cytoscape, ID Mapping, Identifiers, BridgeDb 2 version 2 (revision) 06 Aug 2018 view view version 1 11 Jun 2018 view 1. Ruth Isserlin view gateway. view , University of Toronto, Toronto, Canada 2. Augustin Luna , Dana-Farber Cancer Institute, Boston, USA 3. Nadezhda Doncheva This article is included in the Cytoscape 3 , University of Copenhagen, Copenhagen, Denmark Any reports and responses or comments on the article can be found at the end of the article. Page 1 of 13 F1000Research 2018, 7:725 Last updated: 19 JAN 2024 Corresponding author: Alexander R. Pico () Author roles: Treister A: Methodology, Software, Writing – Original Draft Preparation; Pico AR: Conceptualization, Funding Acquisition, Methodology, Project Administration, Resources, Supervision, Validation, Writing – Original Draft Preparation, Writing – Review & Editing Competing interests: No competing interests were disclosed. Grant information: We would like to acknowledge funding from National Institute of General Medical Sciences [P41GM103504 (ARP, AT)] The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Copyright: © 2018 Treister A and Pico AR. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. How to cite this article: Treister A and Pico AR. Identifier Mapping in Cytoscape: idmapper [version 1; peer review: 1 approved, 2 approved with reservations] F1000Research 2018, 7:725 https://doi.org/10.12688/f1000research.14807.1 First published: 11 Jun 2018, 7:725 https://doi.org/10.12688/f1000research.14807.1 Page 2 of 13 F1000Research 2018, 7:725 Last updated: 19 JAN 2024 Introduction Cytoscape is an integrated network visualization tool and analysis platform1,2. Within its common workflows, identifier mapping remains a challenge when working with biological data from different sources. This problem has been addressed by the BridgeDB project3, which created clients and services to translate between various identifiers. The original BridgeDb app4 for Cytoscape was written to provide an exhaustive set of functions to match the full capabilities of BridgeDb. Though this provided the needed functionality, its basic usage was unnecessarily complex. The idmapper app is a useful alternative, providing a subset of critical features with a simplified interface bundled into Cytoscape. Now, without any installation or configuration, Cytoscape users can rightclick on a table header to map that column’s data to a different namespace (Figure 1). Although, the breadth of coverage is smaller than the full-featured BridgeDb app, it still covers over a dozen identifier data sources, including Ensembl, EntrezGene, HGNC, KEGG, Uniprot and various specied-specific sources. Because idmapper supports Cytoscape’s new CyREST interface, identifier mapping can be included in scripted workflows, and driven from R or python programs. Implementation Inferring the data source From within Cytoscape, a user initiates an ID mapping operation by right-clicking on the header of a column containing identifiers in the Table Panel. In the most common cases the type of identifier can be guessed by idmapper based on the its format. Table 1 shows the supported data sources and example identifier formats. The app looks at the first ten entries and choose the source from the option that matches corresponding regular expressions. This number of identifiers iteratively sampled is set by a static variable called N_Iterations. The algorithm for inferring the data source is implemented in IdGuess.java. Cytoscape tasks There are two different tasks supported by the idmapper app. ColumnMappingTask is activated by the right-click mouse event on a table header. It infers the current table and column from the information that comes from the mouse event. In order to support automation, we added MapColumnCommandTask as an analog that is exposed specifically for Commands and CyREST access. These tasks eventually result in the same algorithms being invoked. Use cases Cytoscape graphical user interface (GUI) The idmapper app provides the same basic functionality of the BridgeDb app with less fuss. Users do not have to install it, launch it, make configuration decisions or think about which database they are accessing. The app comes bundled with every Cytoscape release. As such it usage in Cytoscape via the interactive GUI (graphical user interface) is documented in the Cytoscape manual, http://manual.cytoscape.org/en/stable/Node_and_Edge_Column_ Data.html#mapping-identifiers. To map an identifier from one source to another, right click on the column header of your identifier. Select the option to Map Column to bring up the idmapper dialog (Figure 1). The idmapper dialog presents a few choices the user can override before performing ID mapping. The default Species is determined by the previous selection made per network, providing a “smart and sticky” behavior. The Figure 1. Simplified dialog for ID Mapping. Four options are presented to the user when accessing idmapper from within the Cytoscape GUI, each with common default or inferred values to reduce the number of steps required of the user. Page 3 of 13 F1000Research 2018, 7:725 Last updated: 19 JAN 2024 Table 1. Supported Data Sources. Currently supported identifier databases, their BridgeDb system codes, their species specificity and an example identifier. Data Source Code Species Example Ensembl En Any ENSG00000139618 Entrez Gene L Any 11234 FlyBase F Drosophila melanogaster FBgn0011293 HGNC H Homo sapiens DAPK1 KEGG Genes Kg Any syn:ssr3451 MG M Mus musculus MGI:244229 (...truncated)