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These methods represented an important step forward in sequence assembly, as they both use algorithms to reach a global optimum instead of a local optimum. While both of these methods made progress towards better assemblies, the De Bruijn graph method has become the most popular in the age of next-generation sequencing.
This design is very different from that of Sanger sequencing—also known as capillary sequencing or first-generation sequencing—which is based on electrophoretic separation of chain-termination products produced in individual sequencing reactions. [6] This methodology allows sequencing to be completed on a larger scale. [7]
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 ...
An important part of the design of variant calling methods using NGS data is the DNA sequence used as a reference to which the NGS reads are aligned. In human genetics studies, high quality references are available, from sources such as the HapMap project , [ 10 ] which can substantially improve the accuracy of the variant calls made by variant ...
Most high-throughput, next generation sequencing platforms produce shorter read lengths compared to Sanger sequencing.These new platforms are able to generate large quantities of data in short periods of time, but until methods were developed for de novo assembly of large genomes from short read sequences, Sanger sequencing remained the standard method of creating a reference genome. [10]
In the case of next-generation sequencing methods, library preparation is required before processing. [151] Assessing the quality and quantity of nucleic acids both after extraction and after library preparation identifies degraded, fragmented, and low-purity samples and yields high-quality sequencing data. [152]
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.
In bioinformatics, sequence assembly refers to aligning and merging fragments from a longer DNA sequence in order to reconstruct the original sequence. [1] This is needed as DNA sequencing technology might not be able to 'read' whole genomes in one go, but rather reads small pieces of between 20 and 30,000 bases, depending on the technology used. [1]