title: A curated transcriptome dataset collection to investigate the immunobiology of HIV infection.
abstract: Compendia of large-scale datasets available in public repositories provide an opportunity to identify and fill current gaps in biomedical knowledge. But first, these data need to be readily accessible to research investigators for interpretation. Here, we make available a collection of transcriptome datasets relevant to HIV infection. A total of 2717 unique transcriptional profiles distributed among 34 datasets were identified, retrieved from the NCBI Gene Expression Omnibus (GEO), and loaded in a custom web application, the Gene Expression Browser (GXB), designed for interactive query and visualization of integrated large-scale data. Multiple sample groupings and rank lists were created to facilitate dataset query and interpretation via this interface. Web links to customized graphical views can be generated by users and subsequently inserted in manuscripts reporting novel findings, such as discovery notes. The tool also enables browsing of a single gene across projects, which can provide new perspectives on the role of a given molecule across biological systems. This curated dataset collection is available at: http://hiv.gxbsidra.org/dm3/geneBrowser/list.
authors.affiliation: Sidra Medical and Research Center, Doha, Qatar.
authors.forename: Jana
authors.initials: J
authors.lastname: Blazkova
authors.affiliation: Sidra Medical and Research Center, Doha, Qatar.
authors.forename: Sabri
authors.initials: S
authors.lastname: Boughorbel
authors.affiliation: Benaroya Research Institute, Research Technology, Seattle, WA, USA.
authors.forename: Scott
authors.initials: S
authors.lastname: Presnell
authors.affiliation: Benaroya Research Institute, Research Technology, Seattle, WA, USA.
authors.forename: Charlie
authors.initials: C
authors.lastname: Quinn
authors.affiliation: Sidra Medical and Research Center, Doha, Qatar.
authors.forename: Damien
authors.initials: D
authors.lastname: Chaussabel
keywords: Big Data; Bioinformatics; HIV; Immune Response; Software; Transcriptomics