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RNA-Seq (named as an abbreviation of RNA sequencing) is a technique that uses next-generation sequencing to reveal the presence and quantity of RNA molecules in a biological sample, providing a snapshot of gene expression in the sample, also known as transcriptome. [2] [3]
It uses the seed-and-vote mapping paradigm to determine the mapping location of the read by using its largest mappable region. It automatically decides whether the read should be globally mapped or locally mapped. For RNA-seq data, Subread should be used for the purpose of expression analysis. Subread can also be used to map DNA-seq reads.
DESeq2 is a software package in the field of bioinformatics and computational biology for the statistical programming language R.It is primarily employed for the analysis of high-throughput RNA sequencing (RNA-seq) data to identify differentially expressed genes between different experimental conditions.
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 ...
Normally, in a traditional RNA-seq, microarray, or SAGE experiment RNA is extracted from a biological sample such as cultured cells, and the RNA is analyzed using the chosen method. The data obtained from such an experiment corresponds to abundance of RNA under the given experimental conditions at the time of harvest.
3' mRNA-seq is a quantitative, genome-wide transcriptomic technique based on the barcoding of the 3' untranslated region (UTR) of mRNA molecules. Unlike standard bulk RNA-seq, where short sequencing reads are generated along the entire length of mRNA transcripts, only the 3' end of polyadenylated RNAs are sequenced in 3' mRNA-seq.
Thus, the examples above would be a multi-FASTA file if taken together. Modern bioinformatics programs that rely on the FASTA format expect the sequence headers to be preceded by ">". The sequence is generally represented as "interleaved", or on multiple lines as in the above example, but may also be "sequential", or on a single line.
Originally designed for metagenomic data analysis, MG-RAST also extends support to amplicon sequences (16S, 18S, and ITS) and metatranscriptome (RNA-seq) sequences processing. However, it's important to note that MG-RAST currently lacks the capability to predict coding regions from eukaryotes, limiting its utility for eukaryotic metagenome ...