CandiSNPer: a web tool for the identification of candidate SNPs for causal variants.

Bioinformatics

Department for Crop and Animal Sciences, Humboldt-Universität zu Berlin, Invalidenstrasse 42, 10115 Berlin, Germany.

Published: April 2010

Summary: Human single nucleotide polymorphism (SNP) chips which are used in genome-wide association studies (GWAS) permit the genotyping of up to 4 million SNPs simultaneously. To date, about 1000 human SNPs have been identified as statistically significantly associated with a disease or another trait of interest. The identified SNP is not necessarily the causal variant, but it is rather in linkage disequilibrium (LD) with it. CandiSNPer is a software tool that determines the LD region around a significant SNP from a GWAS. It provides a list with functional annotation and LD values for the SNPs found in the LD region. This list contains not only the SNPs for which genotyping data are available, but all SNPs with rs-IDs, thus increasing the likelihood to include the causal variant. Furthermore, plots showing the LD values are generated. CandiSNPer facilitates the preselection of candidate SNPs for causal variants.

Availability And Implementation: The CandiSNPer server is freely available at http://www2.hu-berlin.de/wikizbnutztier/software/CandiSNPer. The source code is available to academic users 'as is' upon request. The web site is implemented in Perl and R and runs on an Apache server. The Ensembl database is queried for SNP data via Perl APIs.

Download full-text PDF

Source
http://dx.doi.org/10.1093/bioinformatics/btq068DOI Listing

Publication Analysis

Top Keywords

candidate snps
8
snps causal
8
causal variant
8
snps
7
candisnper
4
candisnper web
4
web tool
4
tool identification
4
identification candidate
4
causal
4

Similar Publications

Brassica villosa is characterized by its dense hairiness and high resistance against the fungal pathogen Sclerotinia sclerotiorum. Information on the genetic and molecular mechanisms governing trichome development in B. villosa is rare.

View Article and Find Full Text PDF

Natural hybridisation among rare or endangered species and stable congenerics is increasingly topical for the conservation of species-level diversity under anthropogenic impacts. Evidence for beneficial genes being introgressed into or selected for in hybrids raises concurrent questions about its evolutionary significance. In Darwin's tree finches on the island of Floreana (Galapagos Islands, Ecuador), the Critically Endangered medium tree finch () undergoes introgression with the stable small tree finch (), and hybrids regularly backcross with Earlier studies in 2005-2013 documented an increase in the frequency of hybridisation on Floreana using field-based and microsatellite data.

View Article and Find Full Text PDF

Wheat, a major cereal crop, is the most consumed staple food after rice in India. Frequent episodes of heat waves during the past decade have raised concerns about food security under impending global warming and necessitate the development of heat-tolerant wheat cultivars. Wild relatives of crop plants serve as untapped reservoirs of novel genetic variations.

View Article and Find Full Text PDF

Exploring the causal relationship between inflammatory cytokines, metabolites, and Behcet's syndrome: Mendelian randomization.

Cytokine

January 2025

Department of Periodontology and Oral Mucosa, The Second Affiliated Hospital of Harbin Medical University, Harbin, China; Heilongjiang Provincial Key Laboratory of Hard Tissue Development and Regeneration, The Second Affiliated Hospital of Harbin Medical University, Harbin, China. Electronic address:

Introduction: Behcet's syndrome, as a vasculitic disease involving multiple systems, often induces oral mucosal ulcers. However, levels of inflammatory cytokines and metabolites are unknown for the probability of developing the disease. This study aims to reveal the causal relationship between the cytokines and metabolites and Behcet's syndrome through Mendelian randomization analysis.

View Article and Find Full Text PDF

Rapid and accurate multi-phenotype imputation for millions of individuals.

Nat Commun

January 2025

Key Laboratory of Healthy Mariculture for the East China Sea, Ministry of Agriculture and Rural Affairs & Fisheries college, Jimei University, Xiamen, Fujian, People's Republic of China.

Deep phenotyping can enhance the power of genetic analysis, including genome-wide association studies (GWAS), but the occurrence of missing phenotypes compromises the potential of such resources. Although many phenotypic imputation methods have been developed, the accurate imputation of millions of individuals remains challenging. In the present study, we have developed a multi-phenotype imputation method based on mixed fast random forest (PIXANT) by leveraging efficient machine learning (ML)-based algorithms.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!