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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
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BioXpress: an integrated RNA-seq-derived gene expression database for pan-cancer analysis.

Quan Wan1, Hayley Dingerdissen1, Yu Fan1

  • 1Department of Biochemistry and Molecular Medicine and McCormick Genomic and Proteomic Center, The George Washington University, Washington, DC 20037, USA.

Database : the Journal of Biological Databases and Curation
|March 31, 2015
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Summary

BioXpress is a comprehensive gene expression database linking RNA-seq data to 64 cancer types. It identifies differentially expressed genes, aiding cancer research and pan-cancer analysis.

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Area of Science:

  • Bioinformatics
  • Genomics
  • Cancer Research

Background:

  • Gene expression data is crucial for understanding cancer.
  • Existing databases may lack comprehensive pan-cancer analysis or integrated RNA-seq data.

Purpose of the Study:

  • To develop BioXpress, a unified database for gene expression and cancer associations.
  • To facilitate pan-cancer analysis through standardized data and search functionalities.

Main Methods:

  • Integrated RNA-seq data from TCGA, ICGC, and Expression Atlas.
  • Manual biocuration of publications for cancer association annotations.
  • Mapped cancer types to Disease Ontology terms for uniform analysis.

Main Results:

  • The database contains expression data for 64 cancer types, 6361 patients, and 17,469 genes.
  • 9513 genes showed differential expression between tumor and normal samples.
  • User-friendly search by gene symbol, accession, or cancer type.

Conclusions:

  • BioXpress provides a valuable resource for cancer gene expression analysis.
  • The database supports straightforward retrieval of cancer-related genes and facilitates pan-cancer research.