Dataset Information

AncestrySNPminer: a bioinformatics tool to retrieve and develop ancestry informative SNP panels.

ABSTRACT: A wealth of genomic information is available in public and private databases. However, this information is underutilized for uncovering population specific and functionally relevant markers underlying complex human traits. Given the huge amount of SNP data available from the annotation of human genetic variation, data mining is a faster and cost effective approach for investigating the number of SNPs that are informative for ancestry. In this study, we present AncestrySNPminer, the first web-based bioinformatics tool specifically designed to retrieve Ancestry Informative Markers (AIMs) from genomic data sets and link these informative markers to genes and ontological annotation classes. The tool includes an automated and simple "scripting at the click of a button" functionality that enables researchers to perform various population genomics statistical analyses methods with user friendly querying and filtering of data sets across various populations through a single web interface. AncestrySNPminer can be freely accessed at https://research.cchmc.org/mershalab/AncestrySNPminer/login.php.

SUBMITTER: Amirisetty S

PROVIDER: S-EPMC3433799 | biostudies-literature | 2012 Jul

REPOSITORIES: biostudies-literature

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Publications

AncestrySNPminer: a bioinformatics tool to retrieve and develop ancestry informative SNP panels.

Amirisetty Sushil S Hershey Gurjit K Khurana GK Baye Tesfaye M TM

Genomics 20120511 1

A wealth of genomic information is available in public and private databases. However, this information is underutilized for uncovering population specific and functionally relevant markers underlying complex human traits. Given the huge amount of SNP data available from the annotation of human genetic variation, data mining is a faster and cost effective approach for investigating the number of SNPs that are informative for ancestry. In this study, we present AncestrySNPminer, the first web-bas ...[more]

PMID: 22584067

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Project description:The development of high-throughput sequencing technologies is dramatically increasing the use of single nucleotide polymorphisms (SNPs) across the field of genetics, but most parentage studies of wild populations still rely on microsatellites. We developed a bioinformatic pipeline for identifying SNP panels that are informative for parentage analysis from restriction site-associated DNA sequencing (RADseq) data. This pipeline includes options for analysis with or without a reference genome, and provides methods to maximize genotyping accuracy and select sets of unlinked loci that have high statistical power. We test this pipeline on small populations of Mexican gray wolf and bighorn sheep, for which parentage analyses are expected to be challenging due to low genetic diversity and the presence of many closely related individuals. We compare the results of parentage analysis across SNP panels generated with or without the use of a reference genome, and between SNPs and microsatellites. For Mexican gray wolf, we conducted parentage analyses for 30 pups from a single cohort where samples were available from 64% of possible mothers and 53% of possible fathers, and the accuracy of parentage assignments could be estimated because true identities of parents were known a priori based on field data. For bighorn sheep, we conducted maternity analyses for 39 lambs from five cohorts where 77% of possible mothers were sampled, but true identities of parents were unknown. Analyses with and without a reference genome produced SNP panels with ≥95% parentage assignment accuracy for Mexican gray wolf, outperforming microsatellites at 78% accuracy. Maternity assignments were completely consistent across all SNP panels for the bighorn sheep, and were 74.4% consistent with assignments from microsatellites. Accuracy and consistency of parentage analysis were not reduced when using as few as 284 SNPs for Mexican gray wolf and 142 SNPs for bighorn sheep, indicating our pipeline can be used to develop SNP genotyping assays for parentage analysis with relatively small numbers of loci.

Project description:We detail the development of the ancestry informative single nucleotide polymorphisms (SNPs) panel forming part of the VISAGE Basic Tool (BT), which combines 41 appearance predictive SNPs and 112 ancestry predictive SNPs (three SNPs shared between sets) in one massively parallel sequencing (MPS) multiplex, whereas blood-based age analysis using methylation markers is run in a parallel MPS analysis pipeline. The selection of SNPs for the BT ancestry panel focused on established forensic markers that already have a proven track record of good sequencing performance in MPS, and the overall SNP multiplex scale closely matched that of existing forensic MPS assays. SNPs were chosen to differentiate individuals from the five main continental population groups of Africa, Europe, East Asia, America, and Oceania, extended to include differentiation of individuals from South Asia. From analysis of 1000 Genomes and HGDP-CEPH samples from these six population groups, the BT ancestry panel was shown to have no classification error using the Bayes likelihood calculators of the Snipper online analysis portal. The differentiation power of the component ancestry SNPs of BT was balanced as far as possible to avoid bias in the estimation of co-ancestry proportions in individuals with admixed backgrounds. The balancing process led to very similar cumulative population-specific divergence values for Africa, Europe, America, and Oceania, with East Asia being slightly below average, and South Asia an outlier from the other groups. Comparisons were made of the African, European, and Native American estimated co-ancestry proportions in the six admixed 1000 Genomes populations, using the BT ancestry panel SNPs and 572,000 Affymetrix Human Origins array SNPs. Very similar co-ancestry proportions were observed down to a minimum value of 10%, below which, low-level co-ancestry was not always reliably detected by BT SNPs. The Snipper analysis portal provides a comprehensive population dataset for the BT ancestry panel SNPs, comprising a 520-sample standardised reference dataset; 3445 additional samples from 1000 Genomes, HGDP-CEPH, Simons Foundation and Estonian Biocentre genome diversity projects; and 167 samples of six populations from in-house genotyping of individuals from Middle East, North and East African regions complementing those of the sampling regimes of the other diversity projects.

Dataset Information

AncestrySNPminer: a bioinformatics tool to retrieve and develop ancestry informative SNP panels.

Publications

AncestrySNPminer: a bioinformatics tool to retrieve and develop ancestry informative SNP panels.

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