TCGAbiolinksGUI: A graphical user interface to analyze cancer molecular and clinical data

Silva, Tiago C.; Colaprico, Antonio; Olsen, Catharina; Malta, Tathiane; Bontempi, Gianluca; Ceccarelli, Michele; Berman, Benjamin B.P.; Noushmehr, Houtan

doi:10.12688/f1000research.14197.1

Cited by 21 publications

(32 citation statements)

References 18 publications

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“…We used TCGAbiolinks, an R/Bioconductor software (http://bioconductor.org/packages/release/bioc/ html/TCGAbiolinks.html) [13] and the interphase TCGAbiolinksGUI [14] to download genomic and clinical data of both normal and solid tumor tissues for two different types of cancer from TCGA. Selected cancer types were lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD).…”

Section: Rna-seq and Clinical Information Data From The Cancer Genomementioning

confidence: 99%

Schwann cell reprogramming and lung cancer progression: a meta-analysis of transcriptome data

et al. 2019

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Schwann cells were identified in the tumor surrounding area prior to initiate the invasion process underlying connective tissue. These cells promote cancer invasion through direct contact, while paracrine signaling and matrix remodeling are not sufficient to proceed. Considering the intertwined structure of signaling, regulatory, and metabolic processes within a cell, we employed a genome-scale biomolecular network. Accordingly, a meta-analysis of Schwann cells associated transcriptomic datasets was performed, and the core information on differentially expressed genes (DEGs) was obtained by statistical analyses. Gene set over-representation analyses was performed on core DEGs to identify significantly functional and pathway enrichment analysis between Schwann cells and, lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). DEGs were further integrated with genomescale human biomolecular networks. miRNAs were proposed by the reconstruction of a transcriptional and post-transcriptional regulatory network. Moreover, microarraybased transcriptome profiling was performed, and the prognostic power of selected dedifferentiated Schwann cell biomolecules was predicted. We observed that pathways associated with Schwann cells dedifferentiation was overexpressed in lung cancer samples. However, genes associated with Schwann cells migration inhibition system were downregulated. Besides, miRNA targeting those pathways were also deregulated. In this study, we report valuable data for further experimental and clinical analysis, because the proposed biomolecules have significant potential as systems biomarkers for screening or for therapeutic purposes in perineural invasion of lung cancer.

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Section: Rna-seq and Clinical Information Data From The Cancer Genomementioning

confidence: 99%

Schwann cell reprogramming and lung cancer progression: a meta-analysis of transcriptome data

et al. 2019

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“…In addition, TCGAbiolinks provides integrative methodologies to perform several important downstream analyses (summarized in Table 2). A user-friendly, web-based graphical user interface (GUI) version is also available: the TCGAbiolinksGUI [23]. This interface enables user access to the methodologies offered in TCGAbiolinks using a ‘point-and-click’ style analysis without the need to write specific programming codes.…”

Section: Development Of Molecular Diagnostic Prognostic and Predictivmentioning

confidence: 99%

Clinical and Research Applications of a Brain Tumor Tissue Bank in the Age of Precision Medicine

et al. 2019

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Marked progress has been made recently in the treatment of patients with central nervous system (CNS) tumors, especially gliomas. However, because of the relative rarity of these tumors compared with other malignancies, advances in the molecular/genetic analysis leading to future targeted treatments rely on systematic, organized tissue banking. Several large multi-institutional efforts have utilized major tissue banks that have yielded valuable information that may lead to a better understanding of the pathogenesis of CNS tumors. This manuscript portrays best practices for the establishment and maintenance of a well-organized CNS tumor bank. In addition, annotation for clinical and research needs is explained. The potential benefits to clinical care, as well as basic science and translational research are also described.

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“…, 2015) for cohort selection and data importing from the NCI Genomic Data Commons (Grossman et al. , 2016), (iii) integration with our TCGABiolinksGUI tool (Silva et al. , 2018) to run ELMER via a web-based interface, (iv) output of all results in a single interactive HTML file include all data tables, figures and source code, (v) adoption of software engineering best practices including unit testing and better exception handling, (vi) annotation of cell-type specific chromatin context for resulting genomic elements and (vii) a new Supervised mode where the user can explicitly define sample groups for comparison.…”

Section: Introductionmentioning

confidence: 99%

ELMER v.2: an R/Bioconductor package to reconstruct gene regulatory networks from DNA methylation and transcriptome profiles

et al. 2018

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Motivation DNA methylation has been used to identify functional changes at transcriptional enhancers and other cis-regulatory modules (CRMs) in tumors and other disease tissues. Our R/Bioconductor package ELMER (Enhancer Linking by Methylation/Expression Relationships) provides a systematic approach that reconstructs altered gene regulatory networks (GRNs) by combining enhancer methylation and gene expression data derived from the same sample set. Results We present a completely revised version 2 of ELMER that provides numerous new features including an optional web-based interface and a new Supervised Analysis mode to use pre-defined sample groupings. We show that Supervised mode significantly increases statistical power and identifies additional GRNs and associated Master Regulators, such as SOX11 and KLF5 in Basal-like breast cancer. Availability and implementation ELMER v.2 is available as an R/Bioconductor package at http://bioconductor.org/packages/ELMER/. Supplementary information Supplementary data are available at Bioinformatics online.

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TCGAbiolinksGUI: A graphical user interface to analyze cancer molecular and clinical data

Cited by 21 publications

References 18 publications

Schwann cell reprogramming and lung cancer progression: a meta-analysis of transcriptome data

Schwann cell reprogramming and lung cancer progression: a meta-analysis of transcriptome data

Clinical and Research Applications of a Brain Tumor Tissue Bank in the Age of Precision Medicine

ELMER v.2: an R/Bioconductor package to reconstruct gene regulatory networks from DNA methylation and transcriptome profiles

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