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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 ]
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.
The word transcriptome is a portmanteau of the words transcript and genome.It appeared along with other neologisms formed using the suffixes -ome and -omics to denote all studies conducted on a genome-wide scale in the fields of life sciences and technology.
The word "transcriptome" was first used in the 1990s. [19] [20] In 1995, one of the earliest sequencing-based transcriptomic methods was developed, serial analysis of gene expression (SAGE), which worked by Sanger sequencing of concatenated random transcript fragments. [21] Transcripts were quantified by matching the fragments to known genes.
Paired-end and long-read sequencing of the same sample can mitigate the deficits in short read sequencing by serving as a template or skeleton. Metrics to assess the quality of a de novo assembly include median contig length, number of contigs and N50. [66] RNA-Seq alignment with intron-split short reads.
Trajectory inference as implemented in Slingshot for (a) a simulated two-dimensional dataset and (b) a single-cell RNA-seq dataset of the olfactory epithelium.. Trajectory inference or pseudotemporal ordering is a computational technique used in single-cell transcriptomics to determine the pattern of a dynamic process experienced by cells and then arrange cells based on their progression ...
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In summary, this spatial transcriptomics protocol combines paralleled sequencing and staining of the same sample [3]. In the downstream analysis, bioinformatic tools allow overlay of the tissue image with the gene expression. The output is a map of the transcriptome captured gene expression within a tissue section.