This GTEx version includes RNA-Seq data from 17,382 samples of 54 tissues from 948 post-mortem donors. GTEx version 8.0 RNA-Seq gene read count and TPM-normalised expression data (phs000424.v8.p2, released), as well as their corresponding metadata, were downloaded from GTEx Portal, which offers high-quality curated RNA-Seq data from various human tissues, processed with the same protocol, and ArrayExpress. Public transcriptomic databases offer an ever-increasing amount of primary datasets which, if used for coexpression analysis, can produce findings that transcend the scope of each original experiment. RNA-Seq samples are procured either through in-house experiments or downloaded from public repositories, such as Gene Expression Omnibus (GEO), Sequence Read Archive (SRA), ArrayExpress, Expression Atlas, European Nucleotide Archive (ENA), The Cancer Genome Atlas (TCGA), and Genotype-Tissue Expression (GTEx). Depending on the type of samples used, coexpression analysis can be classified into two approaches: “condition-independent”, where primary data derive from healthy samples from a variety of tissues of an organism, and “condition-dependent”, where the samples come from a specific tissue or experimental condition. As a consequence, RNA-Seq raw data constitute the main source for gene coexpression analysis. RNA-Seq transcriptomic technology can massively study all transcripts of a tissue and has become the norm in gene expression estimation. Gene coexpression analysis is performed on a specific organism, and uses samples from the same transcriptomic platform, that are processed in the same manner. It offers a simple and intuitive website design and user interface, as well as an API endpoint. HGCA2.0 creates working hypotheses for the discovery of gene partners or common biological processes that can be experimentally validated. Benchmarking showed that HGCA2.0 belongs to the top performing coexpression webtools, as shown by STRING analysis. HGCA2.0 has been successful in identifying not only genes with ubiquitous expression patterns, but also tissue-specific genes. HGCA2.0 presents subclades of coexpressed genes to a gene of interest, and performs various built-in gene term enrichment analyses on the coexpressed genes, including gene ontologies, biological pathways, protein families, and diseases, while also being unique in revealing enriched transcription factors driving coexpression. The website is based on the hierarchical clustering of 55,431 Homo sapiens genes based on a large-scale coexpression analysis of 3500 GTEx bulk RNA-Seq samples of healthy individuals, which were selected as the best representative samples of each tissue type. Human Gene Coexpression Analysis 2.0 (HGCA2.0) is a webtool which studies the global coexpression landscape of human genes. Genes with similar expression patterns in a set of diverse samples may be considered coexpressed.
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