The relative affordability of these high-throughput sequencers and the potential to generate large amounts of sequence data at lower cost means that scientists outside of traditional sequencing facilities are now faced with the challenges associated with design of large-scale projects and analysis of the data generated.
The Genome Sequencer FLX (GS FLX) is a sequencing system generating large amounts of sequence data through massively parallel pyrosequencing [2], [3], [4].
Most novel loci exhibit low expression, and are undergoing pseudogenization or subfunctionalization. Comparatively, A. thaliana has lost large amounts of sequence through deletion, particularly of transposable elements.
This has resulted in the accumulation of such large amounts of sequence data that computer-assisted methods, with programs directed toward the manipulation of nucleic acid sequences, have become indispensable during the collection and analysis of that data.
A rapid development of NGS(Next generation Sequencing) technologies can be able to produce large amounts of sequence data,which is leading in to a wide range of new applications.
The increasing numbers of human EST sequences necessitated the development of new computer algorithms to analyze large amounts of sequence data, and in 1993 at The Institute for Genomic Research (TIGR), an algorithm was developed that permitted assembly and analysis of hundreds of thousands of ESTs.
Due to advances in next generation sequencing technology [25], large amounts of sequence variant data are now becoming available, particularly focused on the discovery of rare pathogenic variants.
The current spate of genome sequencing projects [1] has resulted in large amounts of sequence information from all kingdoms of life.
Our research relies heavily on the large amounts of sequence data, and gene and protein analysis software, made available by large research centres for the use of other research scientists.
In recent years, new sequencing technologies have emerged which offer great promise for marker discovery due to their ability to efficiently generate large amounts of sequence data, both in terms of time and cost.
