Integrating, summarizing and visualizing GWAS-hits and human diversity with DANCE (Disease-ANCEstry networks)

Araújo, Gilderlanio Santana de; Lima, Lucas Ramos Costa; Schneider, Silvana; Leal, Thiago P.; Silva, Ana Paula Couto da; Melo, Pedro O. S. Vaz de; Tarazona‐Santos, Eduardo; Scliar, Marília de Oliveira; Rodrigues, Maíra R.

doi:10.1093/bioinformatics/btv708

Cited by 13 publications

(13 citation statements)

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“…This is a difficult multi-class classification challenge, with only a few attempts at the problem. This problem is also related to the issue of separating admixture populations [ 7 , 8 , 40 , 41 ], and recent approaches that have used GWAS (Genome-Wide Association Studies) data [ 2 , 3 , 41 ]. We do not address the problem of admixture in the current paper, and we do not use GWAS datasets.…”

Section: Introductionmentioning

confidence: 99%

Human ancestry indentification under resource constraints -- what can one chromosome tell us about human biogeographical ancestry?

2018

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BackgroundWhile continental level ancestry is relatively simple using genomic information, distinguishing between individuals from closely associated sub-populations (e.g., from the same continent) is still a difficult challenge.MethodsWe study the problem of predicting human biogeographical ancestry from genomic data under resource constraints. In particular, we focus on the case where the analysis is constrained to using single nucleotide polymorphisms (SNPs) from just one chromosome. We propose methods to construct such ancestry informative SNP panels using correlation-based and outlier-based methods.ResultsWe accessed the performance of the proposed SNP panels derived from just one chromosome, using data from the 1000 Genome Project, Phase 3. For continental-level ancestry classification, we achieved an overall classification rate of 96.75% using 206 single nucleotide polymorphisms (SNPs). For sub-population level ancestry prediction, we achieved an average pairwise binary classification rates as follows: subpopulations in Europe: 76.6% (58 SNPs); Africa: 87.02% (87 SNPs); East Asia: 73.30% (68 SNPs); South Asia: 81.14% (75 SNPs); America: 85.85% (68 SNPs).ConclusionOur results demonstrate that one single chromosome (in particular, Chromosome 1), if carefully analyzed, could hold enough information for accurate prediction of human biogeographical ancestry. This has significant implications in terms of the computational resources required for analysis of ancestry, and in the applications of such analyses, such as in studies of genetic diseases, forensics, and soft biometrics.

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Section: Introductionmentioning

confidence: 99%

Human ancestry indentification under resource constraints -- what can one chromosome tell us about human biogeographical ancestry?

2018

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“…We obtained a graph representation of the genetic architecture of BMI using the DANCE web tool (Disease-ANCEstry Networks, http://gilderlanio.pythonanywhere.com/home, Araújo et al 2016), a network-based computational approach to integrate, summarize and visualize GWAS-Catalog-hits (https://www.ebi.ac.uk/gwas/) and 1000G allele frequency information for different populations. We also used DANCE to visualize the genetic architecture of associated genes.…”

Section: Dance Analysismentioning

confidence: 99%

“…For instance, a meta-analysis of genome-wide association studies (GWAS) of BMI estimated that 97 loci explain around 2.7% of its variance (Locke et al 2015). The GWAS-Catalog (Welter et al 2014) and the DANCE web tool (Araújo et al 2016) report 389 SNPs associated with BMI in different populations, with a mean effect size of 0.054 kg/m 2 ( Figure S1).…”

Section: Introductionmentioning

confidence: 99%

Admixture/fine-mapping in Brazilians reveals a West African associated potential regulatory variant (rs114066381) with a strong female-specific effect on body mass- and fat mass-indexes

Scliar

Anna

Santolalla

et al. 2019

Preprint

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Admixed populations are a resource to study the global genetic architecture of complex phenotypes, which is critical, considering that non-European populations are severely underrepresented in genomic studies. Leveraging admixture in Brazilians, whose chromosomes are mosaics of fragments of Native American, European and African origins, we used genome-wide data to perform admixture mapping/fine-mapping of Body Mass Index (BMI) in three population-based cohorts from Northeast (Salvador), Southeast (Bambuí) and South (Pelotas) of the country. We found significant associations with African-associated alleles in children from Salvador (PALD1 and ZMIZ1 genes), and in young adults from Pelotas (NOD2 and MTUS2 genes). More importantly, in Pelotas, rs114066381, mapped in a potential regulatory region, is significantly associated only in females (p= 2.76 e-06). This variant is very rare in Europeans but with frequencies of ~3% in West Africa, and has one of the stronger female-specific effects ever reported (95%CI: 2.32-5.65 kg/m 2 per each A allele). We replicated this sex-specific association and its strong effect for an adjusted fat-mass index in the same Pelotas cohort, and for BMI in another Brazilian cohort from São Paulo (Southeast Brazil). A meta-analysis confirmed the significant association. Remarkably, we observed that while the frequency of rs114066381-A allele ranges from 0.8 to 2.1% in the studied populations, it attains ~9% among morbidly obese women from Pelotas, São Paulo, and Bambuí. The effect size of rs114066381 is at least fivetimes the effect size of the FTO SNPs rs9939609 and rs1558902, already emblematic for their high effects, and for which we replicated associations in Pelotas. We demonstrate how, after a decade of GWAS mostly performed in European-ancestry populations, non-European and admixed populations are a source of new relevant phenotype-associated genetic variants.

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“…For instance, population stratification can confound the relationship between a genetic marker and disease. Identifying ancestry informative markers (AIMs) in the genome is essentially useful for detecting such stratification in case-control association studies of complex diseases, such as diabetes, cardiovascular disease and cancer [1,2,3]. Measuring genetic ancestry has also been a focus in forensic community.…”

Section: Table Of Contentsmentioning

confidence: 99%

“…This is a difficult multi-class classification challenge, with only a few attempts at the problem. This problem is also related to the issue of separating admixture populations [7,35], and recent approaches that have used GWAS (Genome-Wide Association Studies) data [2,3,36]. However, we do not address the problem of admixture in the scope of this work and also, we do not use GWAS datasets.…”

Section: Prior Work and Challengesmentioning

confidence: 99%

Inference of Biogeographical Ancestry Under Resource Constraints

Toma¹

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INFERENCE OF BIOGEPGRAPHICAL ANCESTRY UNDER RESOURCE CONSTRAINTS Tanjin Taher TomaWe study the problem of predicting human biogeographical ancestry using genomic data. While continental level ancestry prediction is relatively simple using genomic information, distinguishing between individuals from closely associated sub-populations (e.g., from the same continent) is still a difficult challenge. In particular, we focus on the case where the analysis is constrained to using single nucleotide polymorphisms (SNPs) from just one chromosome. We thus propose methods to construct ancestry informative SNP panels analyzing variants from a single chromosome, and evaluate the performance of such panels for both continental-level and sub-continental level ancestry prediction.Efficient selection of ancestry informative SNPs is the key to successful ancestry prediction. The removal of redundant and noisy SNP features is essential prior to applying a learning algorithm. Here we propose two distinct methods of SNP selection: one is correlation-based SNP selection which uses a correlation metric to evaluate the usefulness of SNP features, while the other is random subspace projection based SNP selection which uses the learning algorithm itself to evaluate the worth of the SNP features. Correlation-based SNP selection approach can construct a small panel of useful SNPs for both continental level classification as well as binary classification of subpopulations. Unlike the correlation-based selection, random subspace projection based selection can construct efficient panel of SNP markers to address the difficult task of multinomial classification with multiple closely related sub-populations. We include results that demonstrate the performance of both methods, including comparison with other recently published related methods.iii ACKNOWLEDGEMENTS

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Integrating, summarizing and visualizing GWAS-hits and human diversity with DANCE (Disease-ANCEstry networks)

Abstract: Supplementary data are available at Bioinformatics online.

Cited by 13 publications

References 5 publications

Human ancestry indentification under resource constraints -- what can one chromosome tell us about human biogeographical ancestry?

Human ancestry indentification under resource constraints -- what can one chromosome tell us about human biogeographical ancestry?

Admixture/fine-mapping in Brazilians reveals a West African associated potential regulatory variant (rs114066381) with a strong female-specific effect on body mass- and fat mass-indexes

Inference of Biogeographical Ancestry Under Resource Constraints

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