8,801 research outputs found
High-Density Genotypes of Inbred Mouse Strains: Improved Power and Precision of Association Mapping.
Human genome-wide association studies have identified thousands of loci associated with disease phenotypes. Genome-wide association studies also have become feasible using rodent models and these have some important advantages over human studies, including controlled environment, access to tissues for molecular profiling, reproducible genotypes, and a wide array of techniques for experimental validation. Association mapping with common mouse inbred strains generally requires 100 or more strains to achieve sufficient power and mapping resolution; in contrast, sample sizes for human studies typically are one or more orders of magnitude greater than this. To enable well-powered studies in mice, we have generated high-density genotypes for ∼175 inbred strains of mice using the Mouse Diversity Array. These new data increase marker density by 1.9-fold, have reduced missing data rates, and provide more accurate identification of heterozygous regions compared with previous genotype data. We report the discovery of new loci from previously reported association mapping studies using the new genotype data. The data are freely available for download, and Web-based tools provide easy access for association mapping and viewing of the underlying intensity data for individual loci
Towards Better Understanding of Artifacts in Variant Calling from High-Coverage Samples
Motivation: Whole-genome high-coverage sequencing has been widely used for
personal and cancer genomics as well as in various research areas. However, in
the lack of an unbiased whole-genome truth set, the global error rate of
variant calls and the leading causal artifacts still remain unclear even given
the great efforts in the evaluation of variant calling methods.
Results: We made ten SNP and INDEL call sets with two read mappers and five
variant callers, both on a haploid human genome and a diploid genome at a
similar coverage. By investigating false heterozygous calls in the haploid
genome, we identified the erroneous realignment in low-complexity regions and
the incomplete reference genome with respect to the sample as the two major
sources of errors, which press for continued improvements in these two areas.
We estimated that the error rate of raw genotype calls is as high as 1 in
10-15kb, but the error rate of post-filtered calls is reduced to 1 in 100-200kb
without significant compromise on the sensitivity.
Availability: BWA-MEM alignment: http://bit.ly/1g8XqRt; Scripts:
https://github.com/lh3/varcmp; Additional data:
https://figshare.com/articles/Towards_better_understanding_of_artifacts_in_variating_calling_from_high_coverage_samples/981073Comment: Published versio
2b-RAD genotyping for population genomic studies of Chagas disease vectors: Rhodnius ecuadoriensis in Ecuador
Background:
Rhodnius ecuadoriensis is the main triatomine vector of Chagas disease, American trypanosomiasis, in Southern Ecuador and Northern Peru. Genomic approaches and next generation sequencing technologies have become powerful tools for investigating population diversity and structure which is a key consideration for vector control. Here we assess the effectiveness of three different 2b restriction site-associated DNA (2b-RAD) genotyping strategies in R. ecuadoriensis to provide sufficient genomic resolution to tease apart microevolutionary processes and undertake some pilot population genomic analyses.
Methodology/Principal findings:
The 2b-RAD protocol was carried out in-house at a non-specialized laboratory using 20 R. ecuadoriensis adults collected from the central coast and southern Andean region of Ecuador, from June 2006 to July 2013. 2b-RAD sequencing data was performed on an Illumina MiSeq instrument and analyzed with the STACKS de novo pipeline for loci assembly and Single Nucleotide Polymorphism (SNP) discovery. Preliminary population genomic analyses (global AMOVA and Bayesian clustering) were implemented. Our results showed that the 2b-RAD genotyping protocol is effective for R. ecuadoriensis and likely for other triatomine species. However, only BcgI and CspCI restriction enzymes provided a number of markers suitable for population genomic analysis at the read depth we generated. Our preliminary genomic analyses detected a signal of genetic structuring across the study area.
Conclusions/Significance:
Our findings suggest that 2b-RAD genotyping is both a cost effective and methodologically simple approach for generating high resolution genomic data for Chagas disease vectors with the power to distinguish between different vector populations at epidemiologically relevant scales. As such, 2b-RAD represents a powerful tool in the hands of medical entomologists with limited access to specialized molecular biological equipment.
Author summary:
Understanding Chagas disease vector (triatomine) population dispersal is key for the design of control measures tailored for the epidemiological situation of a particular region. In Ecuador, Rhodnius ecuadoriensis is a cause of concern for Chagas disease transmission, since it is widely distributed from the central coast to southern Ecuador. Here, a genome-wide sequencing (2b-RAD) approach was performed in 20 specimens from four communities from Manabí (central coast) and Loja (southern) provinces of Ecuador, and the effectiveness of three type IIB restriction enzymes was assessed. The findings of this study show that this genotyping methodology is cost effective in R. ecuadoriensis and likely in other triatomine species. In addition, preliminary population genomic analysis results detected a signal of population structure among geographically distinct communities and genetic variability within communities. As such, 2b-RAD shows significant promise as a relatively low-tech solution for determination of vector population genomics, dynamics, and spread
Scalable Privacy-Preserving Data Sharing Methodology for Genome-Wide Association Studies
The protection of privacy of individual-level information in genome-wide
association study (GWAS) databases has been a major concern of researchers
following the publication of "an attack" on GWAS data by Homer et al. (2008)
Traditional statistical methods for confidentiality and privacy protection of
statistical databases do not scale well to deal with GWAS data, especially in
terms of guarantees regarding protection from linkage to external information.
The more recent concept of differential privacy, introduced by the
cryptographic community, is an approach that provides a rigorous definition of
privacy with meaningful privacy guarantees in the presence of arbitrary
external information, although the guarantees may come at a serious price in
terms of data utility. Building on such notions, Uhler et al. (2013) proposed
new methods to release aggregate GWAS data without compromising an individual's
privacy. We extend the methods developed in Uhler et al. (2013) for releasing
differentially-private -statistics by allowing for arbitrary number of
cases and controls, and for releasing differentially-private allelic test
statistics. We also provide a new interpretation by assuming the controls' data
are known, which is a realistic assumption because some GWAS use publicly
available data as controls. We assess the performance of the proposed methods
through a risk-utility analysis on a real data set consisting of DNA samples
collected by the Wellcome Trust Case Control Consortium and compare the methods
with the differentially-private release mechanism proposed by Johnson and
Shmatikov (2013).Comment: 28 pages, 2 figures, source code available upon reques
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