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RNA-Seq [1] [2] [3] is a technique [4] that allows transcriptome studies (see also Transcriptomics technologies) based on next-generation sequencing technologies. This technique is largely dependent on bioinformatics tools developed to support the different steps of the process.
RNA-Seq can also be used to determine exon/intron boundaries and verify or amend previously annotated 5' and 3' gene boundaries. Recent advances in RNA-Seq include single cell sequencing, bulk RNA sequencing, [6] 3' mRNA-sequencing, in situ sequencing of fixed tissue, and native RNA molecule sequencing with single-molecule real-time sequencing. [7]
Superfast and accurate read aligners. Subread can be used to map both gDNA-seq and RNA-seq reads. Subjunc detects exon-exon junctions and maps RNA-seq reads. They employ a novel mapping paradigm named seed-and-vote. Yes Yes Yes Yes Free, GPL 3 Taipan De-novo assembler for Illumina reads Proprietary, freeware for academic and noncommercial use UGENE
TopHat is an open-source bioinformatics tool for the throughput alignment of shotgun cDNA sequencing reads generated by transcriptomics technologies (e.g. RNA-Seq) using Bowtie first and then mapping to a reference genome to discover RNA splice sites de novo. [1] TopHat aligns RNA-Seq reads to mammalian-sized genomes. [2]
Standard pipeline to extract variants from an individual's genome Sequencing machines able to identify the sequence of bases constituting the DNA. The massive reduction in sequencing costs [2] resulted in a significant increase in the size and the availability of genomics data [3] with the potential of revolutionizing many fields, from medicine to drug design.
STARR-seq (short for self-transcribing active regulatory region sequencing) is a method to assay enhancer activity for millions of candidates from arbitrary sources of DNA. It is used to identify the sequences that act as transcriptional enhancers in a direct, quantitative, and genome-wide manner.
Time-resolved RNA sequencing methods are applications of RNA-seq that allow for observations of RNA abundances over time in a biological sample or samples. Second-Generation DNA sequencing has enabled cost effective, high throughput and unbiased analysis of the transcriptome . [ 1 ]
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.