We present a novel method for simultaneous genotype calling and haplotype-phase inference. Our method employs the computationally efficient BEAGLE haplotype-frequency model, which can be applied to large-scale studies with millions of markers and thousands of samples. We compare genotype calls made with our method to genotype calls made with the BIRDSEED, CHIAMO, GenCall, and ILLUMINUS genotype-calling methods, using genotype data from the Illumina 550K and Affymetrix 500K arrays. We show that our method has higher genotype-call accuracy and yields fewer uncalled genotypes than competing methods. We perform single-marker analysis of data from the Wellcome Trust Case Control Consortium bipolar disorder and type 2 diabetes studies. For bipola...
In this paper we propose algorithmic strategies, Lander-Waterman-like statistical estimates, and gen...
Many existing cohorts contain a range of relatedness between genotyped individuals, either by design...
In this paper we propose algorithmic strategies, Lander-Waterman-like statistical estimates, and gen...
Genotype microarrays assay hundreds of thousands of genetic variants on an individual's genome. The ...
Whole-genome association studies present many new statistical and computational challenges due to th...
We present methods for imputing data for ungenotyped markers and for inferring haplotype phase in la...
The genome-wide association study (GWAS) has become a routine approach for mapping disease risk loci...
Phasing is the process of inferring haplotypes from genotype data. Efficient algorithms and associat...
Motivation: Large-scale genotyping relies on the use of unsuper-vised automated calling algorithms t...
MOTIVATION: Given the current costs of next-generation sequencing, large studies carry out low-cover...
The accuracy of the vast amount of genotypic information generated by high-throughput genotyping tec...
Emerging sequencing technologies allow common and rare variants to be systematically assayed across ...
<div><p>Many existing cohorts contain a range of relatedness between genotyped individuals, either b...
Many existing cohorts contain a range of relatedness between genotyped individuals, either by design...
The valuable information in correct order of alleles on the haplotypes has many applications in GWAS...
In this paper we propose algorithmic strategies, Lander-Waterman-like statistical estimates, and gen...
Many existing cohorts contain a range of relatedness between genotyped individuals, either by design...
In this paper we propose algorithmic strategies, Lander-Waterman-like statistical estimates, and gen...
Genotype microarrays assay hundreds of thousands of genetic variants on an individual's genome. The ...
Whole-genome association studies present many new statistical and computational challenges due to th...
We present methods for imputing data for ungenotyped markers and for inferring haplotype phase in la...
The genome-wide association study (GWAS) has become a routine approach for mapping disease risk loci...
Phasing is the process of inferring haplotypes from genotype data. Efficient algorithms and associat...
Motivation: Large-scale genotyping relies on the use of unsuper-vised automated calling algorithms t...
MOTIVATION: Given the current costs of next-generation sequencing, large studies carry out low-cover...
The accuracy of the vast amount of genotypic information generated by high-throughput genotyping tec...
Emerging sequencing technologies allow common and rare variants to be systematically assayed across ...
<div><p>Many existing cohorts contain a range of relatedness between genotyped individuals, either b...
Many existing cohorts contain a range of relatedness between genotyped individuals, either by design...
The valuable information in correct order of alleles on the haplotypes has many applications in GWAS...
In this paper we propose algorithmic strategies, Lander-Waterman-like statistical estimates, and gen...
Many existing cohorts contain a range of relatedness between genotyped individuals, either by design...
In this paper we propose algorithmic strategies, Lander-Waterman-like statistical estimates, and gen...