Search results
Results from the WOW.Com Content Network
Data management: A single RNA-Seq experiment in humans is usually 1-5 Gb (compressed), or more when including intermediate files. [59] This large volume of data can pose storage issues. One solution is compressing the data using multi-purpose computational schemas (e.g., gzip) or genomics-specific schemas. The latter can be based on reference ...
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 ...
An RNA timestamp is a technology that enables the age of any given RNA transcript to be inferred by exploiting RNA editing. [1] In this technique, the RNA of interest is tagged to an adenosine rich reporter motif that consists of multiple MS2 binding sites. These MS2 binding sites recruit a complex composed of ADAR2 (adenosine deaminase acting ...
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.
RNA-seq is emerging (2013) as the method of choice for measuring transcriptomes of organisms, though the older technique of DNA microarrays is still used. [1] RNA-seq measures the transcription of a specific gene by converting long RNAs into a library of cDNA fragments. The cDNA fragments are then sequenced using high-throughput sequencing ...
At this step, sequencing reads whose quality have been improved are mapped to a reference genome using alignment tools like BWA [17] for short DNA sequence reads, minimap [18] for long read DNA sequences, and STAR [19] for RNA sequence reads. The purpose of mapping is to find the origin of any given read based on the reference sequence.
RNA Seq Experiment. The single-cell RNA-seq technique converts a population of RNAs to a library of cDNA fragments. These fragments are sequenced by high-throughput next generation sequencing techniques and the reads are mapped back to the reference genome, providing a count of the number of reads associated with each gene. [13]
Inchworm assembles the RNA-Seq data into transcript sequences, often generating full-length transcripts for a dominant isoform, but then reports just the unique portions of alternatively spliced transcripts. Chrysalis clusters the Inchworm contigs and constructs complete de Bruijn graphs for each cluster. Each cluster represents the full ...