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TBro: visualization and management of de novo transcriptomes

Zitieren Sie bitte immer diese URN: urn:nbn:de:bvb:20-opus-147954
  • RNA sequencing (RNA-seq) has become a powerful tool to understand molecular mechanisms and/or developmental programs. It provides a fast, reliable and cost-effective method to access sets of expressed elements in a qualitative and quantitative manner. Especially for non-model organisms and in absence of a reference genome, RNA-seq data is used to reconstruct and quantify transcriptomes at the same time. Even SNPs, InDels, and alternative splicing events are predicted directly from the data without having a reference genome at hand. A keyRNA sequencing (RNA-seq) has become a powerful tool to understand molecular mechanisms and/or developmental programs. It provides a fast, reliable and cost-effective method to access sets of expressed elements in a qualitative and quantitative manner. Especially for non-model organisms and in absence of a reference genome, RNA-seq data is used to reconstruct and quantify transcriptomes at the same time. Even SNPs, InDels, and alternative splicing events are predicted directly from the data without having a reference genome at hand. A key challenge, especially for non-computational personnal, is the management of the resulting datasets, consisting of different data types and formats. Here, we present TBro, a flexible de novo transcriptome browser, tackling this challenge. TBro aggregates sequences, their annotation, expression levels as well as differential testing results. It provides an easy-to-use interface to mine the aggregated data and generate publication-ready visualizations. Additionally, it supports users with an intuitive cart system, that helps collecting and analysing biological meaningful sets of transcripts. TBro’s modular architecture allows easy extension of its functionalities in the future. Especially, the integration of new data types such as proteomic quantifications or array-based gene expression data is straightforward. Thus, TBro is a fully featured yet flexible transcriptome browser that supports approaching complex biological questions and enhances collaboration of numerous researchers.zeige mehrzeige weniger

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Metadaten
Autor(en): Markus J. Ankenbrand, Lorenz Weber, Dirk Becker, Frank Förster, Felix Bemm
URN:urn:nbn:de:bvb:20-opus-147954
Dokumentart:Artikel / Aufsatz in einer Zeitschrift
Institute der Universität:Fakultät für Biologie / Theodor-Boveri-Institut für Biowissenschaften
Sprache der Veröffentlichung:Englisch
Titel des übergeordneten Werkes / der Zeitschrift (Englisch):Database
Erscheinungsjahr:2016
Band / Jahrgang:2016
Seitenangabe:baw146
Originalveröffentlichung / Quelle:Database, 2016, 1–7 doi: 10.1093/database/baw146
DOI:https://doi.org/10.1093/database/baw146
Allgemeine fachliche Zuordnung (DDC-Klassifikation):0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Freie Schlagwort(e):database
Datum der Freischaltung:08.06.2017
Sammlungen:Open-Access-Publikationsfonds / Förderzeitraum 2016
Lizenz (Deutsch):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung