<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>
doi: 10.1038/ng1558
pmid: 15920530
Genome-wide association studies with SNP markers are expected to allow identification of genes that underlie complex disorders. Hundreds of thousands of SNP markers will be required for comprehensive genome-wide association studies. The development of microarray-based methods for SNP genotyping on this scale remains a demanding task, despite many recent advances in technology for the production of high-density microarrays. A key technical obstacle is the PCR amplification step, which is required to reduce the complexity of and gain sufficient sensitivity for genotyping SNPs in large, diploid genomes. The multiplexing level that can be achieved in PCR does not match that of current microarray-based methods, making PCR the limiting step in the assays. Highly multiplexed microarray systems for SNP genotyping have recently been developed by combining well-known reaction principles for DNA amplification and SNP genotyping in clever ways. These new methods offer the potential of genome-wide SNP mapping of genes involved in complex diseases in the foreseeable future, provided that issues related to selection of the optimal SNP markers, sample throughput and the cost of the assays can be addressed.
Ligases, Genome, Genotype, Humans, DNA-Directed DNA Polymerase, Polymerase Chain Reaction, Polymorphism, Single Nucleotide, Oligonucleotide Array Sequence Analysis
Ligases, Genome, Genotype, Humans, DNA-Directed DNA Polymerase, Polymerase Chain Reaction, Polymorphism, Single Nucleotide, Oligonucleotide Array Sequence Analysis
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 391 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 1% | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 0.1% |