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A lot of emphasis has been given to RNA-Seq data after the Encyclopedia of DNA Elements (ENCODE) and The Cancer Genome Atlas (TCGA) projects have used this approach to characterize dozens of cell lines [154] and thousands of primary tumor samples, [155] respectively. ENCODE aimed to identify genome-wide regulatory regions in different cohort of ...
queryable-rna-seq-database Formally known as the Queryable RNA-Seq Database, this system is designed to simplify the process of RNA-seq analysis by providing the ability upload the result data from RNA-Seq analysis into a database, store it, and query it in many different ways.
These three databases are primary databases, as they house original sequence data. They collaborate with Sequence Read Archive (SRA), which archives raw reads from high-throughput sequencing instruments. Secondary databases are: [clarification needed] 23andMe's database; HapMap; OMIM (Online Mendelian Inheritance in Man): inherited diseases; RefSeq
Database of long-noncoding RNAs causally implicated in cancer through in vivo, in vitro and other evidence. [15] BIGTranscriptome: High-confidence of coding and noncoding transcriptomes assembled with hundreds of pseudo-stranded and stranded RNA-seq datasets. [16] lncRNAKB
The Reference Sequence (RefSeq) database [1] is an open access, annotated and curated collection of publicly available nucleotide sequences (DNA, RNA) and their protein products. RefSeq was introduced in 2000.
Currently RNA-Seq relies on copying RNA molecules into cDNA molecules prior to sequencing; therefore, the subsequent platforms are the same for transcriptomic and genomic data. Consequently, the development of DNA sequencing technologies has been a defining feature of RNA-Seq. [ 78 ] [ 80 ] [ 81 ] Direct sequencing of RNA using nanopore ...