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RseqFlow is an RNA-Seq analysis pipeline which offers an express implementation of analysis steps for RNA sequencing datasets. It can perform pre and post mapping quality control (QC) for sequencing data, calculate expression levels for uniquely mapped reads, identify differentially expressed genes, and convert file formats for ease of ...
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.
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.
Name Description Knots [Note 1]Links References trRosettaRNA: trRosettaRNA is an algorithm for automated prediction of RNA 3D structure. It builds the RNA structure by Rosetta energy minimization, with deep learning restraints from a transformer network (RNAformer). trRosettaRNA has been validated in blind tests, including CASP15 and RNA-Puzzles, which suggests that the automated predictions ...
TopHat is used to align reads from an RNA-Seq experiment. It is a read-mapping algorithm and it aligns the reads to a reference genome. It is useful because it does not need to rely on known splice sites. [1] TopHat can be used with the Tuxedo pipeline, and is frequently used with Bowtie.
Analysis of CLIP sequencing data benefits from use of customised computational software, much of which is available as part of the Nextflow pipeline for CLIP analysis, and specialised software is available for rapid demultiplexing of complex multiplexed libraries, [15] comparative visualisation of crosslinking profiles across RNAs, [16 ...
Whereas high sequence coverage for a genome may indicate the presence of repetitive sequences (and thus be masked), for a transcriptome, they may indicate abundance. In addition, unlike genome sequencing, transcriptome sequencing can be strand-specific, due to the possibility of both sense and antisense transcripts. Finally, it can be difficult ...
In regard to data analysis after sequencing, a computational pipeline known as dropSeqPipe was developed by the McCarroll Lab at Harvard. [6] Although the pipeline was originally developed for use with Drop-seq scRNA-seq data, it can be used with DroNc-Seq data as it also utilizes droplet technology.