SNPs of Setipinna tenuifilis
Ontology highlight
ABSTRACT:
ORGANISM(S): Setipinna tenuifilis
SUBMITTER: Ying
PROVIDER: S-BSST565 | biostudies-other |
SECONDARY ACCESSION(S): 1
REPOSITORIES: biostudies-other
Similar Datasets
Project description:BackgroundThe recent advancement in human genome sequencing and genotyping has revealed millions of single nucleotide polymorphisms (SNP) which determine the variation among human beings. One of the particular important projects is The International HapMap Project which provides the catalogue of human genetic variation for disease association studies. In this paper, we analyzed the genotype data in HapMap project by using National Institute of Environmental Health Sciences Environmental Genome Project (NIEHS EGP) SNPs. We first determine whether the HapMap data are transferable to the NIEHS data. Then, we study how well the HapMap SNPs capture the untyped SNPs in the region. Finally, we provide general guidelines for determining whether the SNPs chosen from HapMap may be able to capture most of the untyped SNPs.ResultsOur analysis shows that HapMap data are not robust enough to capture the untyped variants for most of the human genes. The performance of SNPs for European and Asian samples are marginal in capturing the untyped variants, i.e. approximately 55%. Expectedly, the SNPs from HapMap YRI panel can only capture approximately 30% of the variants. Although the overall performance is low, however, the SNPs for some genes perform very well and are able to capture most of the variants along the gene. This is observed in the European and Asian panel, but not in African panel. Through observation, we concluded that in order to have a well covered SNPs reference panel, the SNPs density and the association among reference SNPs are important to estimate the robustness of the chosen SNPs.ConclusionWe have analyzed the coverage of HapMap SNPs using NIEHS EGP data. The results show that HapMap SNPs are transferable to the NIEHS SNPs. However, HapMap SNPs cannot capture some of the untyped SNPs and therefore resequencing may be needed to uncover more SNPs in the missing region.
| S-EPMC1586200 | biostudies-literature
Project description:Genotype calls for 78 human breast tumor cases. Keywords: Human Breast tissue
2006-02-09 | GSE3743 | GEO
Project description:We propose that haplotyped loci with high heterozygosity can be useful in human identification, especially within families, if recombination is very low among the sites. Three or more SNPs extending over small molecular intervals (<10 KB) can be identified in the human genome to define miniature haplotypes with moderate levels of linkage disequilibrium. Properly selected, these mini-haplotypes (or minihaps) consist of multiple haplotype lineages (alleles) that have evolved from the ancestral human haplotype but show no evidence of recurring recombination, allowing each distinct haplotype to be equated with an allele, all copies of which are essentially identical by descent. Historic recombinants, representing rare events that have drifted to common frequencies over many generations, can be identified in some cases, they do not equate to frequently recurring recombination. We have identified examples in our data collected on various projects and present eight such mini-haplotypes comprised of informative SNPs. We also discuss the ideal characteristics and advantages of minihaps for human familial identification and ancestry inference, and compare them to other types of forensic markers in use and/or that have been proposed. We expect that it is possible to carry out a systematic search and identify a useful panel of mini-haplotypes, with even better properties than the examples presented here.
| S-EPMC3476707 | biostudies-literature
Project description:Genetic variation in the human genome is an emerging resource for studying cancer, a complex set of diseases characterised by both environmental and genetic contributions. The number of common germ-line variants is great, on the order of 10-15 million per person, and represents a remarkable opportunity to investigate the aetiology, interindividual differences in treatment response and outcomes of specific cancers. The study of genetic variation can elucidate critical determinants in environmental exposure and cancer, which could have future implications for preventive and early intervention strategies. However, we are in the initial stages of characterising the tools (i.e., the single-nucleotide polymorphism, SNP) to rigorously analyse the genetic contributions to complex diseases, such as cancer. If the promise of the genomic era is to be realised, we must integrate this information into new strategies for implementation in both public health measures and, most importantly, provision of individual cancer-related care.
| S-EPMC2410167 | biostudies-other
Project description:The utility of short tandem repeat genetic (STR) markers for forensic science is beyond question and there are over 50 million STR profiles in current national databases. The magnitude and value of those data, however, are likely to be dwarfed by what is emerging from large-scale SNP and DNA sequence assays. Phenotypic characterization may well accompany future statements about identity. In this very brief review we focus on the use of rare variants to describe relatedness and population structure.
| S-EPMC5545933 | biostudies-other
Project description:A major goal of genetic association studies concerned with single nucleotide polymorphisms (SNPs) is the detection of SNPs exhibiting an impact on the risk of developing a disease. Typically, this problem is approached by testing each of the SNPs individually. This, however, can lead to an inaccurate measurement of the influence of the SNPs on the disease risk, in particular, if SNPs only show an effect when interacting with other SNPs, as the multivariate structure of the data is ignored. In this article, we propose a testing procedure based on logic regression that takes this structure into account and therefore enables a more appropriate quantification of importance and ranking of the SNPs than marginal testing. Since even SNP interactions often exhibit only a moderate effect on the disease risk, it can be helpful to also consider sets of SNPs (e.g. SNPs belonging to the same gene or pathway) to borrow strength across these SNP sets and to identify those genes or pathways comprising SNPs that are most consistently associated with the response. We show how the proposed procedure can be adapted for testing SNP sets, and how it can be applied to blocks of SNPs in linkage disequilibrium (LD) to overcome problems caused by LD.
| S-EPMC3006123 | biostudies-literature
Project description:ApoC-III is a proatherogenic protein associated with elevated triglycerides; its deficiency is associated with reduced atherosclerosis. Mixed dyslipidemia, characterized by elevated triglyceride and apoC-III levels and low HDL cholesterol level, with or without elevated LDL cholesterol, increases cardiovascular disease risk and is commonly treated with combined statin and fibrate therapy. We sought to identify single nucleotide polymorphisms (SNPs) associated with apoC-III level response to combination therapy with statins and fenofibric acid (FA) in individuals with mixed dyslipidemia. Participants in a multicenter, randomized, double-blind, active-controlled study examining response to FA alone and in combination with statin were genotyped for candidate SNPs. Association between genotyed SNPs and APOC3 response to therapy was conducted
2012-01-11 | GSE34945 | GEO
Project description:ApoC-III is a proatherogenic protein associated with elevated triglycerides; its deficiency is associated with reduced atherosclerosis. Mixed dyslipidemia, characterized by elevated triglyceride and apoC-III levels and low HDL cholesterol level, with or without elevated LDL cholesterol, increases cardiovascular disease risk and is commonly treated with combined statin and fibrate therapy. We sought to identify single nucleotide polymorphisms (SNPs) associated with apoC-III level response to combination therapy with statins and fenofibric acid (FA) in individuals with mixed dyslipidemia. Participants in a multicenter, randomized, double-blind, active-controlled study examining response to FA alone and in combination with statin were genotyped for candidate SNPs. Association between genotyed SNPs and APOC3 response to therapy was conducted We sought to identify single nucleotide polymorphisms (SNPs) associated with apoC-III level response to combination therapy with statins and fenofibric acid (FA) in individuals with mixed dyslipidemia. Participants in a multicenter, randomized, double-blind, active-controlled study examining response to FA alone and in combination with statin were genotyped for candidate SNPs. Genomic DNA extracted from peripheral blood was genotyped using a custom GoldenGate bead array encompassing 384 SNPs (Illumina). Multivariate linear regression and 2-way ANOVA for percent change in apoC-III level were performed between the groups receiving FA alone compared with FA+statin compared with statin alone.
2012-01-11 | E-GEOD-34945 | biostudies-arrayexpress
Project description:BackgroundRecent development of high-resolution single nucleotide polymorphism (SNP) arrays allows detailed assessment of genome-wide human genome variations. There is increasing recognition of the importance of SNPs for medicine and developmental biology. However, SNP data set typically has a large number of SNPs (e.g., 400 thousand SNPs in genome-wide Parkinson disease data set) and a few hundred of samples. Conventional classification methods may not be effective when applied to such genome-wide SNP data.ResultsIn this paper, we use shrunken dissimilarity measure to analyze and select relevant SNPs for classification problems. Examples of HapMap data and Parkinson disease (PD) data are given to demonstrate the effectiveness of the proposed method, and illustrate it has a potential to become a useful analysis tool for SNP data sets. We use Parkinson disease data as an example, and perform a whole genome analysis. For the 367440 SNPs with less than 1% missing percentage from all 22 chromosomes, we can select 357 SNPs from this data set. For the unique genes that those SNPs are located in, a gene-gene similarity value is computed using GOSemSim and gene pairs that has a similarity value being greater than a threshold are selected to construct several groups of genes. For the SNPs that involved in these groups of genes, a statistical software PLINK is employed to compute the pair-wise SNP-SNP interactions, and SNPs with significance of P < 0.01 are chosen to identify SNPs networks based on their P values. Here SNPs networks are constructed based on Gene Ontology knowledge, and therefore each SNP network plays a role in the biological process. An analysis shows that such networks have relationships directly or indirectly to Parkinson disease.ConclusionsExperimental results show that our approach is suitable to handle genetic variations, and provide useful knowledge in a genome-wide SNP study.
| S-EPMC2982692 | biostudies-literature