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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]
Diceseq Statistical modeling of isoform splicing dynamics from RNA-seq time series data. EBChangepoint An empirical Bayes change-point model for identifying 3′ and 5′ alternative splicing by RNA-Seq. Eoulsan A versatile framework dedicated to high throughput sequencing data analysis. Allows automated analysis (mapping, counting and ...
The term transcriptome is a portmanteau of the words transcript and genome; it is associated with the process of transcript production during the biological process of transcription. The early stages of transcriptome annotations began with cDNA libraries published in the 1980s. Subsequently, the advent of high-throughput technology led to ...
Assembly of RNA-Seq reads is not dependent on a reference genome [122] and so is ideal for gene expression studies of non-model organisms with non-existing or poorly developed genomic resources. For example, a database of SNPs used in Douglas fir breeding programs was created by de novo transcriptome analysis in the absence of a sequenced ...
Time dependence: Gene expression changes over time, and RNA-Seq only takes a snapshot. Time course experiments can be performed to observe changes in the transcriptome. Coverage (also known as depth): RNA harbors the same mutations observed in DNA, and detection requires deeper coverage. With high enough coverage, RNA-Seq can be used to ...
Single-cell transcriptomics makes it possible to unravel heterogeneous cell populations, reconstruct cellular developmental pathways, and model transcriptional dynamics — all previously masked in bulk RNA sequencing. [2]
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The sequencing length of the tag can be freely chosen. Because of this, the tags can be assembled into contigs and the annotation of the tags can be drastically improved. Therefore, MACE is also use for the analyses of non-model organisms. In addition, the longer contigs can be screened for polymorphisms.