ArticleBMC bioinformatics2017
TCGA2BED: extracting, extending, integrating, and querying The Cancer Genome Atlas.
Article in BMC bioinformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Transcriptional analysis of landmark molecular pathways in lung adenocarcinoma results in a clinically relevant classification with potential therapeutic implications.Molecular oncology · 2024Article
- Ten quick tips for avoiding pitfalls in multi-omics data integration analyses.PLoS computational biology · 2023Article
- Breast cancer dormancy is associated with a 4NG1 state and not senescence.NPJ breast cancer · 2021Article
- DriverDBv3: a multi-omics database for cancer driver gene research.Nucleic acids research · 2020Article
- GenoSurf: metadata driven semantic search system for integrated genomic datasets.Database : the journal of biological databases and curation · 2019Article
- CamurWeb: a classification software and a large knowledge base for gene expression data of cancer.BMC bioinformatics · 2018Article
- Integrative Histologic and Bioinformatics Analysis of BIRC5/Survivin Expression in Oral Squamous Cell Carcinoma.International journal of molecular sciences · 2018Article
- Combining DNA methylation and RNA sequencing data of cancer for supervised knowledge extraction.BioData mining · 2018Article
- lncRNA PVT1 identified as an independent biomarker for prognosis surveillance of solid tumors based on transcriptome data and meta-analysis.Cancer management and research · 2018Review
- LncRNA PVT1 as an effective biomarker for cancer diagnosis and detection based on transcriptome data and meta-analysis.Oncotarget · 2017Article
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Authors and funding
5 authors.
Funding
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Abstract
backgroundData extraction and integration methods are becoming essential to effectively access and take advantage of the huge amounts of heterogeneous genomics and clinical data increasingly available. In this work, we focus on The Cancer Genome Atlas, a comprehensive archive of tumoral data containing the results of high-throughout experiments, mainly Next Generation Sequencing, for more than 30 cancer types.
resultsWe propose TCGA2BED a software tool to search and retrieve TCGA data, and convert them in the structured BED format for their seamless use and integration. Additionally, it supports the conversion in CSV, GTF, JSON, and XML standard formats. Furthermore, TCGA2BED extends TCGA data with information extracted from other genomic databases (i.e., NCBI Entrez Gene, HGNC, UCSC, and miRBase). We also provide and maintain an automatically updated data repository with publicly available Copy Number Variation, DNA-methylation, DNA-seq, miRNA-seq, and RNA-seq (V1,V2) experimental data of TCGA converted into the BED format, and their associated clinical and biospecimen meta data in attribute-value text format.
conclusionsThe availability of the valuable TCGA data in BED format reduces the time spent in taking advantage of them: it is possible to efficiently and effectively deal with huge amounts of cancer genomic data integratively, and to search, retrieve and extend them with additional information. The BED format facilitates the investigators allowing several knowledge discovery analyses on all tumor types in TCGA with the final aim of understanding pathological mechanisms and aiding cancer treatments.
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