Research Methods

The RICOPILI pipeline for rapid imputation of consortia-scale genetic association data The RICOPILI pipeline is an open-sourced, Perl-based system that allows the efficient quality control, imputation, and analysis of genome-wide association data from consortia-scle multi-cohort studies. Links to the manuscript, script and tutorials are provided in the links. Citation: Max Lam, Swapnil Awasthi, Hunna J Watson, et al., RICOPILI: Rapid Imputation for COnsortias PIpeLIne, Bioinformatics, Volume 36, Issue 3, 1 February 2020, Pages 930933, https://doi.org/10.1093/bioinformatics/btz633 Natural science - Biology - Genetics - Data imputation Posted by team TransBio from: Zentralinstitut für Seelische Gesundheit

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Extensive Tool for Network Analysis of protein-protein interaction networks Extensive Tool for Network Analysis (ETNA) allows the topological analysis of protein-protein interaction networks in order to detect bias, e.g., caused by scientific trends. Links to the manuscript and the code repository can be found in the link section. Reference: Alicja W Nowakowska, Malgorzata Kotulska, Topological analysis as a tool for detection of abnormalities in proteinprotein interaction data, Bioinformatics, Volume 38, Issue 16, 15 August 2022, Pages 39683975, https://doi.org/10.1093/bioinformatics/btac440 Natural science - Biology - Computational biology - Network analysis Posted by team TransBio from: Zentralinstitut für Seelische Gesundheit

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Biological Random Walks for the prioritization of disease genes in the human interactome The Biological Random Walks (BRW) method allows the integrative, network-based analysis of multiple data modalities, in order to prioritize genes with regards to their potential disease relevance. Links to the manuscript and code can be found in the links section. Citation: Michele Gentili, Leonardo Martini, Marialuisa Sponziello, Luca Becchetti, Biological Random Walks: multi-omics integration for disease gene prioritization, Bioinformatics, Volume 38, Issue 17, 1 September 2022, Pages 41454152, https://doi.org/10.1093/bioinformatics/btac446 Natural science - Biology - Computational biology - Network analysis Posted by team TransBio from: Zentralinstitut für Seelische Gesundheit

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The REALGAR web app of integrated respiratory omics data REALGAR (Reducing Associations by Linking Genes and omics Results) is an integrated omics resource that comprises multi-layered information for gene-centric analysis and visualization of different omics data types in the context of respiratory disease. The links to manuscript, web app and source code can be found in the links section. Citation: Mengyuan Kan, Avantika R Diwadkar, Supriya Saxena, Haoyue Shuai, Jaehyun Joo, Blanca E Himes, REALGAR: a web app of integrated respiratory omics data, Bioinformatics, Volume 38, Issue 18, 15 September 2022, Pages 44424445, https://doi.org/10.1093/bioinformatics/btac524 Applied science - Medicine and health - Respiratory therapy - Data resource Posted by team TransBio from: Zentralinstitut für Seelische Gesundheit

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