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to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
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]
The earliest RNA-Seq work was published in 2006 with one hundred thousand transcripts sequenced using 454 technology. [40] This was sufficient coverage to quantify relative transcript abundance. RNA-Seq began to increase in popularity after 2008 when new Solexa/Illumina technologies allowed one billion transcript sequences to be recorded.
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 ...
to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
The tools used at this stage depend on the sequencing platform. For instance, FastQC checks the quality of short reads (including RNA sequences), Nanoplot or PycoQC are used for long read sequences (e.g. Nanopore sequence reads), and MultiQC aggregates the result of FastQC in a webpage format. [11] [12] [13]
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.
For example, to investigate a biological process which is estimated to occur for an hour, a researcher might design an experiment where the process is triggered for five minutes, 15 minutes, 30 minutes, 45 minutes, one hour, and two hours in separate cell culture samples before harvesting the cells for RNA-seq analysis.
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