Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Detecting structure of haplotypes and local ancestry.

ABSTRACT: We present a two-layer hidden Markov model to detect the structure of haplotypes for unrelated individuals. This allows us to model two scales of linkage disequilibrium (one within a group of haplotypes and one between groups), thereby taking advantage of rich haplotype information to infer local ancestry of admixed individuals. Our method outperforms competing state-of-the-art methods, particularly for regions of small ancestral track lengths. Applying our method to Mexican samples in HapMap3, we found two regions on chromosomes 6 and 8 that show significant departure of local ancestry from the genome-wide average. A software package implementing the methods described in this article is freely available at http://bcm.edu/cnrc/mcmcmc.

SUBMITTER: Guan Y

PROVIDER: S-EPMC3948796 | biostudies-other | 2014 Mar

REPOSITORIES: biostudies-other

ACCESS DATA

Json Xml

Publications

Detecting structure of haplotypes and local ancestry.

Guan Yongtao Y

Genetics 20140103 3

We present a two-layer hidden Markov model to detect the structure of haplotypes for unrelated individuals. This allows us to model two scales of linkage disequilibrium (one within a group of haplotypes and one between groups), thereby taking advantage of rich haplotype information to infer local ancestry of admixed individuals. Our method outperforms competing state-of-the-art methods, particularly for regions of small ancestral track lengths. Applying our method to Mexican samples in HapMap3, ...[more]

PMID: 24388880

Similar Datasets

Use of Plasma ctDNA Methylation Haplotypes in Detecting Local Residual or Lymph Node Metastasis

Project description:This is a prospective, clinical study. This study is to evaluate the sensitivity of plasma ctDNA methylation haplotypes in detecting local residual or lymph node metastasis.

| 2299281 | ecrin-mdr-crc

Detecting individual ancestry in the human genome.

Project description:Detecting and quantifying the population substructure present in a sample of individuals are of main interest in the fields of genetic epidemiology, population genetics, and forensics among others. To date, several algorithms have been proposed for estimating the amount of genetic ancestry within an individual. In the present review, we introduce the most widely used methods in population genetics for detecting individual genetic ancestry. We further show, by means of simulations, the performance of popular algorithms for detecting individual ancestry in various controlled demographic scenarios. Finally, we provide some hints on how to interpret the results from these algorithms.

| S-EPMC4416275 | biostudies-other

Ancestry inference using reference labeled clusters of haplotypes.

Project description:BackgroundWe present ARCHes, a fast and accurate haplotype-based approach for inferring an individual's ancestry composition. Our approach works by modeling haplotype diversity from a large, admixed cohort of hundreds of thousands, then annotating those models with population information from reference panels of known ancestry.ResultsThe running time of ARCHes does not depend on the size of a reference panel because training and testing are separate processes, and the inferred population-annotated haplotype models can be written to disk and reused to label large test sets in parallel (in our experiments, it averages less than one minute to assign ancestry from 32 populations using 10 CPU). We test ARCHes on public data from the 1000 Genomes Project and the Human Genome Diversity Project (HGDP) as well as simulated examples of known admixture.ConclusionsOur results demonstrate that ARCHes outperforms RFMix at correctly assigning both global and local ancestry at finer population scales regardless of the amount of population admixture.

| S-EPMC8466715 | biostudies-literature

Detecting local residue environment similarity for recognizing near-native structure models.

Project description:We developed a new representation of local amino acid environments in protein structures called the Side-chain Depth Environment (SDE). An SDE defines a local structural environment of a residue considering the coordinates and the depth of amino acids that locate in the vicinity of the side-chain centroid of the residue. SDEs are general enough that similar SDEs are found in protein structures with globally different folds. Using SDEs, we developed a procedure called PRESCO (Protein Residue Environment SCOre) for selecting native or near-native models from a pool of computational models. The procedure searches similar residue environments observed in a query model against a set of representative native protein structures to quantify how native-like SDEs in the model are. When benchmarked on commonly used computational model datasets, our PRESCO compared favorably with the other existing scoring functions in selecting native and near-native models.

| S-EPMC4237674 | biostudies-literature

Local ancestry corrects for population structure in Saccharomyces cerevisiae genome-wide association studies.

Project description:Genome-wide association studies (GWAS) have become an important method for mapping the genetic loci underlying complex phenotypic traits in many species. A crucial issue when performing GWAS is to control for the underlying population structure because not doing so can lead to spurious associations. Population structure is a particularly important issue in nonhuman species since it is often difficult to control for population structure during the study design phase, requiring population structure to be corrected statistically after the data have been collected. It has not yet been established if GWAS is a feasible approach in Saccharomyces cerevisiae, an important model organism and agricultural species. We thus performed an empirical study of statistical methods for controlling for population structure in GWAS using a set of 201 phenotypic traits measured in multiple resequenced strains of S. cerevisiae. We complemented our analysis of real data with an extensive set of simulations. Our main result is that a mixed linear model using the local ancestry of the strain as a covariate is effective at controlling for population structure, consistent with the mosaic structure of many S. cerevisiae strains. We further studied the evolutionary forces acting on the GWAS SNPs and found that SNPs associated with variation in phenotypic traits are enriched for low minor allele frequencies, consistent with the action of negative selection on these SNPs. Despite the effectiveness of local ancestry correction, GWAS remains challenging in highly structured populations, such as S. cerevisiae. Nonetheless, we found that, even after correcting for population structure, there is still sufficient statistical power to recover biologically meaningful associations.

| S-EPMC3512155 | biostudies-literature

An ancestry-based approach for detecting interactions.

Project description:BACKGROUND:Epistasis and gene-environment interactions are known to contribute significantly to variation of complex phenotypes in model organisms. However, their identification in human association studies remains challenging for myriad reasons. In the case of epistatic interactions, the large number of potential interacting sets of genes presents computational, multiple hypothesis correction, and other statistical power issues. In the case of gene-environment interactions, the lack of consistently measured environmental covariates in most disease studies precludes searching for interactions and creates difficulties for replicating studies. RESULTS:In this work, we develop a new statistical approach to address these issues that leverages genetic ancestry, defined as the proportion of ancestry derived from each ancestral population (e.g., the fraction of European/African ancestry in African Americans), in admixed populations. We applied our method to gene expression and methylation data from African American and Latino admixed individuals, respectively, identifying nine interactions that were significant at P<5×10-8. We show that two of the interactions in methylation data replicate, and the remaining six are significantly enriched for low P-values (P<1.8×10-6). CONCLUSION:We show that genetic ancestry can be a useful proxy for unknown and unmeasured covariates in the search for interaction effects. These results have important implications for our understanding of the genetic architecture of complex traits.

| S-EPMC6065511 | biostudies-literature

Private haplotypes can reveal local adaptation.

Project description:BACKGROUND: Genome-wide scans for regions that demonstrate deviating patterns of genetic variation have become common approaches for finding genes targeted by selection. Several genomic patterns have been utilized for this purpose, including deviations in haplotype homozygosity, frequency spectra and genetic differentiation between populations. RESULTS: We describe a novel approach based on the Maximum Frequency of Private Haplotypes--MFPH--to search for signals of recent population-specific selection. The MFPH statistic is straightforward to compute for phased SNP- and sequence-data. Using both simulated and empirical data, we show that MFPH can be a powerful statistic to detect recent population-specific selection, that it performs at the same level as other commonly used summary statistics (e.g. FST, iHS and XP-EHH), and that MFPH in some cases capture signals of selection that are missed by other statistics. For instance, in the Maasai, MFPH reveals a strong signal of selection in a region where other investigated statistics fail to pick up a clear signal that contains the genes DOCK3, MAPKAPK3 and CISH. This region has been suggested to affect height in many populations based on phenotype-genotype association studies. It has specifically been suggested to be targeted by selection in Pygmy groups, which are on the opposite end of the human height spectrum compared to the Maasai. CONCLUSIONS: From the analysis of both simulated and publicly available empirical data, we show that MFPH represents a summary statistic that can provide further insight concerning population-specific adaptation.

| S-EPMC4040116 | biostudies-literature

Mini-haplotypes as lineage informative SNPs and ancestry inference SNPs.

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

Local Ancestry Inference in Large Pedigrees.

Project description:Local ancestry, defined as the genetic ancestry at a genomic location of an admixed individual, is widely used as a genetic marker in genetic association and evolutionary genetics studies. Many methods have been developed to infer the local ancestries in a set of unrelated individuals, a few of them have been extended to small nuclear families, but none can be applied to large (e.g. three-generation) pedigrees. In this study, we developed a method, FamANC, that can improve the accuracy of local ancestry inference in large pedigrees by: (1) using an existing algorithm to infer local ancestries for all individuals in a family, assuming (contrary to fact) they are unrelated, and (2) improving its accuracy by correcting inference errors using pedigree structure. Applied on African-American pedigrees from the Cleveland Family Study, FamANC was able to correct all identified Mendelian errors and most of double crossovers.

| S-EPMC6957497 | biostudies-literature

Haplotypes in SLC24A5 Gene as Ancestry Informative Markers in Different Populations.

Project description:Ancestry informative markers (AIMs) are human polymorphisms that exhibit substantially allele frequency differences among populations. These markers can be useful to provide information about ancestry of samples which may be useful in predicting a perpetrator's ethnic origin to aid criminal investigations. Variations in human pigmentation are the most obvious phenotypes to distinguish individuals. It has been recently shown that the variation of a G in an A allele of the coding single-nucleotide polymorphism (SNP) rs1426654 within SLC24A5 gene varies in frequency among several population samples according to skin pigmentation. Because of these observations, the SLC24A5 locus has been evaluated as Ancestry Informative Region (AIR) by typing rs1426654 together with two additional intragenic markers (rs2555364 and rs16960620) in 471 unrelated individuals originating from three different continents (Africa, Asia and Europe). This study further supports the role of human SLC24A5 gene in skin pigmentation suggesting that variations in SLC24A5 haplotypes can correlate with human migration and ancestry. Furthermore, our data do reveal the utility of haplotype and combined unphased genotype analysis of SLC24A5 in predicting ancestry and provide a good example of usefulness of genetic characterization of larger regions, in addition to single polymorphisms, as candidates for population-specific sweeps in the ancestral population.

| S-EPMC2674805 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data