Identical By Descent Segments Research Articles

A fast and accurate method for detection of IBD shared haplotypes in genome-wide SNP data.

Identical by descent (IBD) segments are used to understand a number of fundamental issues in genetics. IBD segments are typically detected using long stretches of identical alleles between haplotypes in phased, whole-genome SNP data. Phase or SNP call errors in genomic data can degrade accuracy of IBD detection and lead to false-positive/negative calls and to under/overextension of true IBD segments. Furthermore, the number of comparisons increases quadratically with sample size, requiring high computational efficiency. We developed a new IBD segment detection program, FISHR (Find IBD Shared Haplotypes Rapidly), in an attempt to accurately detect IBD segments and to better estimate their endpoints using an algorithm that is fast enough to be deployed on very large whole-genome SNP data sets. We compared the performance of FISHR to three leading IBD segment detection programs: GERMLINE, refined IBD, and HaploScore. Using simulated and real genomic sequence data, we show that FISHR is slightly more accurate than all programs at detecting long (>3 cm) IBD segments but slightly less accurate than refined IBD at detecting short (~1 cm) IBD segments. More centrally, FISHR outperforms all programs in determining the true endpoints of IBD segments, which is crucial for several applications of IBD information. FISHR takes two to three times longer than GERMLINE to run, whereas both GERMLINE and FISHR were orders of magnitude faster than refined IBD and HaploScore. Overall, FISHR provides accurate IBD detection in unrelated individuals and is computationally efficient enough to be utilized on large SNP data sets >60 000 individuals.

Exploring Identity-By-Descent Segments and Putative Functions Using Different Foundation Parents in Maize.

Maize foundation parents (FPs) play no-alternative roles in hybrid breeding because they were widely used in the development of new lines and hybrids. The combination of different identity-by-descent (IBD) segments and genes could account for the formation patterns of different FPs, and knowledge of these IBD regions would provide an extensive foundation for the development of new candidate FP lines in future maize breeding. In this paper, a panel of 304 elite lines derived from FPs, i.e., B73, 207, Mo17, and Huangzaosi (HZS), was collected and analyzed using 43,252 single nucleotide polymorphism (SNP) markers. Most IBD segments specific to particular FP groups were identified, including 116 IBD segments in B73, 105 in Mo17, 111 in 207, and 190 in HZS. In these regions, 423 quantitative trait nucleotides (QTNs) associated with 15 agronomic traits and 804 candidate genes were identified. Some known adaptation-related genes, e.g., dwarf8 and vgt1 in HZS, zcn8 and epc in Mo17, and ZmCCT in 207, were validated as being tightly linked to particular IBD segments. In addition, numerous new candidate genes were also identified. For example, GRMZM2G154278 in HZS, which belongs to the cell cycle control family, was closely linked to a QTN of the ear height/plant height (EH/PH) trait; GRMZM2G051943 in 207, which encodes an endochitinase precursor (EP) chitinase, was closely linked to a QTN for kernel density; and GRMZM2G170586 in Mo17 was closely linked to a QTN for ear diameter. Complex correlations among these genes were also found. Many IBD segments and genes were included in the formation of FP lines, and complex regulatory networks exist among them. These results provide new insights on the genetic basis of complex traits and provide new candidate IBD regions or genes for the improvement of special traits in maize production.

IBD Sharing between Africans, Neandertals, and Denisovans.

Interbreeding between ancestors of humans and other hominins outside of Africa has been studied intensively, while their common history within Africa still lacks proper attention. However, shedding light on human evolution in this time period about which little is known, is essential for understanding subsequent events outside of Africa. We investigate the genetic relationships of humans, Neandertals, and Denisovans by identifying very short DNA segments in the 1000 Genomes Phase 3 data that these hominins share identical by descent (IBD). By focusing on low frequency and rare variants, we identify very short IBD segments with high confidence. These segments reveal events from a very distant past because shorter IBD segments are presumably older than longer ones. We extracted two types of very old IBD segments that are not only shared among humans, but also with Neandertals and/or Denisovans. The first type contains longer segments that are found primarily in Asians and Europeans where more segments are found in South Asians than in East Asians for both Neandertal and Denisovan. These longer segments indicate complex admixture events outside of Africa. The second type consists of shorter segments that are shared mainly by Africans and therefore may indicate events involving ancestors of humans and other ancient hominins within Africa. Our results from the autosomes are further supported by an analysis of chromosome X, on which segments that are shared by Africans and match the Neandertal and/or Denisovan genome were even more prominent. Our results indicate that interbreeding with other hominins was a common feature of human evolution starting already long before ancestors of modern humans left Africa.

Robust Inference of Identity by Descent from Exome-Sequencing Data

Identifying and characterizing genomic regions that are shared identical by descent (IBD) among individuals can yield insight into population history, facilitate the identification of adaptively evolving loci, and be an important tool in disease gene mapping. Although increasingly large collections of exome sequences have been generated, it is challenging to detect IBD segments in exomes, precluding many potentially informative downstream analyses. Here, we describe an approach, ExIBD, to robustly detect IBD segments in exome-sequencing data, rigorously evaluate its performance, and apply this method to high-coverage exomes from 6,515 European and African Americans. Furthermore, we show how IBD networks, constructed from patterns of pairwise IBD between individuals, and principles from graph theory provide insight into recent population history and reveal cryptic population structure in European Americans. Our results enable IBD analyses to be performed on exome data, which will expand the scope of inferences that can be made from existing massively large exome-sequencing datasets.

A Genealogical Look at Shared Ancestry on the X Chromosome.

Close relatives can share large segments of their genome identical by descent (IBD) that can be identified in genome-wide polymorphism data sets. There are a range of methods to use these IBD segments to identify relatives and estimate their relationship. These methods have focused on sharing on the autosomes, as they provide a rich source of information about genealogical relationships. We hope to learn additional information about recent ancestry through shared IBD segments on the X chromosome, but currently lack the theoretical framework to use this information fully. Here, we fill this gap by developing probability distributions for the number and length of X chromosome segments shared IBD between an individual and an ancestor k generations back, as well as between half- and full-cousin relationships. Due to the inheritance pattern of the X and the fact that X homologous recombination occurs only in females (outside of the pseudoautosomal regions), the number of females along a genealogical lineage is a key quantity for understanding the number and length of the IBD segments shared among relatives. When inferring relationships among individuals, the number of female ancestors along a genealogical lineage will often be unknown. Therefore, our IBD segment length and number distributions marginalize over this unknown number of recombinational meioses through a distribution of recombinational meioses we derive. By using Bayes' theorem to invert these distributions, we can estimate the number of female ancestors between two relatives, giving us details about the genealogical relations between individuals not possible with autosomal data alone.

Rapidly Registering Identity-by-Descent Across Ancestral Recombination Graphs.

The genomes of remotely related individuals occasionally contain long segments that are identical by descent (IBD). Sharing of IBD segments has many applications in population and medical genetics, and it is thus desirable to study their properties in simulations. However, no current method provides a direct, efficient means to extract IBD segments from simulated genealogies. Here, we introduce computationally efficient approaches to extract ground-truth IBD segments from a sequence of genealogies, or equivalently, an ancestral recombination graph. Specifically, we use a two-step scheme, where we first identify putative shared segments by comparing the common ancestors of all pairs of individuals at some distance apart. This reduces the search space considerably, and we then proceed by determining the true IBD status of the candidate segments. Under some assumptions and when allowing a limited resolution of segment lengths, our run-time complexity is reduced from O(n(3) log n) for the naïve algorithm to O(n log n), where n is the number of individuals in the sample.

Atlas of Cryptic Genetic Relatedness Among 1000 Human Genomes

A novel computational method for detecting identical-by-descent (IBD) chromosomal segments between sequenced genomes is presented. It utilizes the distribution patterns of very rare genetic variants (vrGVs), which have minor allele frequencies <0.2%. Contrary to the existing probabilistic approaches our method is rather deterministic, because it considers a group of very rare events which cannot happen together only by chance. This method has been applied for exhaustive computational search of shared IBD segments among 1,092 sequenced individuals from 14 populations. It demonstrated that clusters of vrGVs are unique and powerful markers of genetic relatedness, that uncover IBD chromosomal segments between and within populations, irrespective of whether divergence was recent or occurred hundreds-to-thousands of years ago. We found that several IBD segments are shared by practically any possible pair of individuals belonging to the same population. Moreover, shared short IBD segments (median size 183 kb) were found in 10% of inter-continental human pairs, each comprising of a person from sub-Saharan Africa and a person from Southern Europe. The shortest shared IBD segments (median size 54 kb) were found in 0.42% of inter-continental pairs composed of individuals from Chinese/Japanese populations and Africans from Kenya and Nigeria. Knowledge of inheritance of IBD segments is important in clinical case–control and cohort studies, since unknown distant familial relationships could compromise interpretation of collected data. Clusters of vrGVs should be useful markers for familial relationship and common multifactorial disorders.

Leveraging Distant Relatedness to Quantify Human Mutation and Gene-Conversion Rates

The rate at which human genomes mutate is a central biological parameter that has many implications for our ability to understand demographic and evolutionary phenomena. We present a method for inferring mutation and gene-conversion rates by using the number of sequence differences observed in identical-by-descent (IBD) segments together with a reconstructed model of recent population-size history. This approach is robust to, and can quantify, the presence of substantial genotyping error, as validated in coalescent simulations. We applied the method to 498 trio-phased sequenced Dutch individuals and inferred a point mutation rate of 1.66 × 10(-8) per base per generation and a rate of 1.26 × 10(-9) for <20 bp indels. By quantifying how estimates varied as a function of allele frequency, we inferred the probability that a site is involved in non-crossover gene conversion as 5.99 × 10(-6). We found that recombination does not have observable mutagenic effects after gene conversion is accounted for and that local gene-conversion rates reflect recombination rates. We detected a strong enrichment of recent deleterious variation among mismatching variants found within IBD regions and observed summary statistics of local sharing of IBD segments to closely match previously proposed metrics of background selection; however, we found no significant effects of selection on our mutation-rate estimates. We detected no evidence of strong variation of mutation rates in a number of genomic annotations obtained from several recent studies. Our analysis suggests that a mutation-rate estimate higher than that reported by recent pedigree-based studies should be adopted in the context of DNA-based demographic reconstruction.

PIGS: improved estimates of identity-by-descent probabilities by probabilistic IBD graph sampling.

Identifying segments in the genome of different individuals that are identical-by-descent (IBD) is a fundamental element of genetics. IBD data is used for numerous applications including demographic inference, heritability estimation, and mapping disease loci. Simultaneous detection of IBD over multiple haplotypes has proven to be computationally difficult. To overcome this, many state of the art methods estimate the probability of IBD between each pair of haplotypes separately. While computationally efficient, these methods fail to leverage the clique structure of IBD resulting in less powerful IBD identification, especially for small IBD segments.We develop a hybrid approach (PIGS), which combines the computational efficiency of pairwise methods with the power of multiway methods. It leverages the IBD graph structure to compute the probability of IBD conditional on all pairwise estimates simultaneously. We show via extensive simulations and analysis of real data that our method produces a substantial increase in the number of identified small IBD segments.

Genotyping of geographically diverse Druze trios reveals substructure and a recent bottleneck.

Druze individuals rarely marry outside their faith (often practicing consanguinity) and are thus believed to form a genetic isolate. To comprehensively characterize the genetic structure of the Druze population, we recruited and genotyped 40 parent-offspring trios from the Upper Galilee in Israel and the Golan Heights, attempting to capture different extended families (clans) across various geographical locations. Principal component (PC) and ADMIXTURE analyses demonstrated that Druze are close to, yet distinct from, other Middle-Eastern groups (Bedouins and Palestinians), supporting the Druze's Middle-Eastern origin and their recent genetic isolation. Reconstruction of the Druze demographic history using identical-by-descent (IBD) segments suggested an ≈15-fold reduction in population size taking place ≈22-47 generations ago, close to the documented time of the foundation of the Druze faith at the 11th century. Combining the Galilee and Golan Druze genotypes with previously published data on Druze from the Carmel (Israel) and Lebanon demonstrated that all four Druze communities are genetically distinct. The Lebanese group shared less IBD segments (within the group and with other groups) compared with the Israeli Druze and showed higher heterozygosity (suggesting less consanguinity), but was less diverse in PC space. These findings suggest complex recent and ancient demographic history of the Druze population.

Parente2: a fast and accurate method for detecting identity by descent

Identity-by-descent (IBD) inference is the problem of establishing a genetic connection between two individuals through a genomic segment that is inherited by both individuals from a recent common ancestor. IBD inference is an important preceding step in a variety of population genomic studies, ranging from demographic studies to linking genomic variation with phenotype and disease. The problem of accurate IBD detection has become increasingly challenging with the availability of large collections of human genotypes and genomes: Given a cohort’s size, a quadratic number of pairwise genome comparisons must be performed. Therefore, computation time and the false discovery rate can also scale quadratically. To enable accurate and efficient large-scale IBD detection, we present Parente2, a novel method for detecting IBD segments. Parente2 is based on an embedded log-likelihood ratio and uses a model that accounts for linkage disequilibrium by explicitly modeling haplotype frequencies. Parente2 operates directly on genotype data without the need to phase data prior to IBD inference. We evaluate Parente2’s performance through extensive simulations using real data, and we show that it provides substantially higher accuracy compared to previous state-of-the-art methods while maintaining high computational efficiency.

A renewal theory approach to IBD sharing

A long genomic segment inherited by a pair of individuals from a single, recent common ancestor is said to be identical-by-descent (IBD). Shared IBD segments have numerous applications in genetics, from demographic inference to phasing, imputation, pedigree reconstruction, and disease mapping. Here, we provide a theoretical analysis of IBD sharing under Markovian approximations of the coalescent with recombination. We describe a general framework for the IBD process along the chromosome under the Markovian models (SMC/SMC’), as well as introduce and justify a new model, which we term the renewal approximation, under which lengths of successive segments are independent. Then, considering the infinite-chromosome limit of the IBD process, we recover previous results (for SMC) and derive new results (for SMC’) for the mean number of shared segments longer than a cutoff and the fraction of the chromosome found in such segments. We then use renewal theory to derive an expression (in Laplace space) for the distribution of the number of shared segments and demonstrate implications for demographic inference. We also compute (again, in Laplace space) the distribution of the fraction of the chromosome in shared segments, from which we obtain explicit expressions for the first two moments. Finally, we generalize all results to populations with a variable effective size.

Identity-by-descent approaches identify regions of importance for genetic susceptibility to hereditary esophageal squamous cell carcinoma.

Worldwide, the highest prevalence of esophageal cancer (EC) occurs in Northern China. High-density SNP arrays allow identification of identity-by-descent (IBD) segments in genomic DNAs representative of shared common ancestral regions. We utilized IBD approaches to map susceptibility loci associated with low-penetrance SNPs in high-risk Henan hereditary esophageal squamous cell carcinoma (ESCC) patients. Affymetrix GeneChip Human mapping SNP array IBD analysis was performed in 32 Henan family history-positive (FH+) ESCC patients, 18 Henan healthy unrelated individuals, and 45 Chinese individuals from a CHB HapMap dataset using PLink (scoring IBD segments individually) and Beagle (scoring of shared IBD segments among case/case vs. control/control pairs) software. Both analyses identified longer IBD segment lengths associated with FH+ ESCC compared to controls. However, there was no strong evidence for a genetic founder effect. Pairing IBD analysis with BEAGLE identified 8 critical IBD segments residing at 2q32.1-q32.2, 3p22.3-p22.2, 4q21.1-q21.21, 7p22.2, 8q23.2-q23.3, 10q23.33-q24.1, 14q24.3 and 16q11.2-q12.1, which were more significantly shared among case/case compared to control/control. The shared IBD segments in FH+ ESCC samples with no overlap with control/CHB Hapmap may encompass potential cancer susceptibility loci. Selected targeted genes, PLCE1, GPT2, SIAH1 and CYP2C-18, residing within the IBD segments at 10q23.33-q24.1 and 16q11.2-q12.1, had statistically significant differential expression in primary ESCC tissues and are likely involved in ESCC carcinogenesis. The importance of these IBD segments to the etiology and development of ESCC in high-risk areas requires further study with expanded sample sizes. This is the first report employing the pairing IBD approach for elucidation of the genetic basis of hereditary ESCC in Henan by applying high throughput SNP array analysis.

Genome-wide mapping of IBD segments in an Ashkenazi PD cohort identifies associated haplotypes.

The recent series of large genome-wide association studies in European and Japanese cohorts established that Parkinson disease (PD) has a substantial genetic component. To further investigate the genetic landscape of PD, we performed a genome-wide scan in the largest to date Ashkenazi Jewish cohort of 1130 Parkinson patients and 2611 pooled controls. Motivated by the reduced disease allele heterogeneity and a high degree of identical-by-descent (IBD) haplotype sharing in this founder population, we conducted a haplotype association study based on mapping of shared IBD segments. We observed significant haplotype association signals at three previously implicated Parkinson loci: LRRK2 (OR = 12.05, P = 1.23 × 10(-56)), MAPT (OR = 0.62, P = 1.78 × 10(-11)) and GBA (multiple distinct haplotypes, OR > 8.28, P = 1.13 × 10(-11) and OR = 2.50, P = 1.22 × 10(-9)). In addition, we identified a novel association signal on chr2q14.3 coming from a rare haplotype (OR = 22.58, P = 1.21 × 10(-10)) and replicated it in a secondary cohort of 306 Ashkenazi PD cases and 2583 controls. Our results highlight the power of our haplotype association method, particularly useful in studies of founder populations, and reaffirm the benefits of studying complex diseases in Ashkenazi Jewish cohorts.

Reducing pervasive false-positive identical-by-descent segments detected by large-scale pedigree analysis.

Analysis of genomic segments shared identical-by-descent (IBD) between individuals is fundamental to many genetic applications, from demographic inference to estimating the heritability of diseases, but IBD detection accuracy in nonsimulated data is largely unknown. In principle, it can be evaluated using known pedigrees, as IBD segments are by definition inherited without recombination down a family tree. We extracted 25,432 genotyped European individuals containing 2,952 father–mother–child trios from the 23andMe, Inc. data set. We then used GERMLINE, a widely used IBD detection method, to detect IBD segments within this cohort. Exploiting known familial relationships, we identified a false-positive rate over 67% for 2–4 centiMorgan (cM) segments, in sharp contrast with accuracies reported in simulated data at these sizes. Nearly all false positives arose from the allowance of haplotype switch errors when detecting IBD, a necessity for retrieving long (>6 cM) segments in the presence of imperfect phasing. We introduce HaploScore, a novel, computationally efficient metric that scores IBD segments proportional to the number of switch errors they contain. Applying HaploScore filtering to the IBD data at a precision of 0.8 produced a 13-fold increase in recall when compared with length-based filtering. We replicate the false IBD findings and demonstrate the generalizability of HaploScore to alternative data sources using an independent cohort of 555 European individuals from the 1000 Genomes project. HaploScore can improve the accuracy of segments reported by any IBD detection method, provided that estimates of the genotyping error rate and switch error rate are available.

An Effective Filter for IBD Detection in Large Data Sets

Identity by descent (IBD) inference is the task of computationally detecting genomic segments that are shared between individuals by means of common familial descent. Accurate IBD detection plays an important role in various genomic studies, ranging from mapping disease genes to exploring ancient population histories. The majority of recent work in the field has focused on improving the accuracy of inference, targeting shorter genomic segments that originate from a more ancient common ancestor. The accuracy of these methods, however, is achieved at the expense of high computational cost, resulting in a prohibitively long running time when applied to large cohorts. To enable the study of large cohorts, we introduce SpeeDB, a method that facilitates fast IBD detection in large unphased genotype data sets. Given a target individual and a database of individuals that potentially share IBD segments with the target, SpeeDB applies an efficient opposite-homozygous filter, which excludes chromosomal segments from the database that are highly unlikely to be IBD with the corresponding segments from the target individual. The remaining segments can then be evaluated by any IBD detection method of choice. When examining simulated individuals sharing 4 cM IBD regions, SpeeDB filtered out 99.5% of genomic regions from consideration while retaining 99% of the true IBD segments. Applying the SpeeDB filter prior to detecting IBD in simulated fourth cousins resulted in an overall running time that was 10,000x faster than inferring IBD without the filter and retained 99% of the true IBD segments in the output.

Relationship estimation from whole-genome sequence data.

The determination of the relationship between a pair of individuals is a fundamental application of genetics. Previously, we and others have demonstrated that identity-by-descent (IBD) information generated from high-density single-nucleotide polymorphism (SNP) data can greatly improve the power and accuracy of genetic relationship detection. Whole-genome sequencing (WGS) marks the final step in increasing genetic marker density by assaying all single-nucleotide variants (SNVs), and thus has the potential to further improve relationship detection by enabling more accurate detection of IBD segments and more precise resolution of IBD segment boundaries. However, WGS introduces new complexities that must be addressed in order to achieve these improvements in relationship detection. To evaluate these complexities, we estimated genetic relationships from WGS data for 1490 known pairwise relationships among 258 individuals in 30 families along with 46 population samples as controls. We identified several genomic regions with excess pairwise IBD in both the pedigree and control datasets using three established IBD methods: GERMLINE, fastIBD, and ISCA. These spurious IBD segments produced a 10-fold increase in the rate of detected false-positive relationships among controls compared to high-density microarray datasets. To address this issue, we developed a new method to identify and mask genomic regions with excess IBD. This method, implemented in ERSA 2.0, fully resolved the inflated cryptic relationship detection rates while improving relationship estimation accuracy. ERSA 2.0 detected all 1st through 6th degree relationships, and 55% of 9th through 11th degree relationships in the 30 families. We estimate that WGS data provides a 5% to 15% increase in relationship detection power relative to high-density microarray data for distant relationships. Our results identify regions of the genome that are highly problematic for IBD mapping and introduce new software to accurately detect 1st through 9th degree relationships from whole-genome sequence data.

Efficient clustering of identity-by-descent between multiple individuals

Most existing identity-by-descent (IBD) detection methods only consider haplotype pairs; less attention has been paid to considering multiple haplotypes simultaneously, even though IBD is an equivalence relation on haplotypes that partitions a set of haplotypes into IBD clusters. Multiple-haplotype IBD clusters may have advantages over pairwise IBD in some applications, such as IBD mapping. Existing methods for detecting multiple-haplotype IBD clusters are often computationally expensive and unable to handle large samples with thousands of haplotypes. We present a clustering method, efficient multiple-IBD, which uses pairwise IBD segments to infer multiple-haplotype IBD clusters. It expands clusters from seed haplotypes by adding qualified neighbors and extends clusters across sliding windows in the genome. Our method is an order of magnitude faster than existing methods and has comparable performance with respect to the quality of clusters it uncovers. We further investigate the potential application of multiple-haplotype IBD clusters in association studies by testing for association between multiple-haplotype IBD clusters and low-density lipoprotein cholesterol in the Northern Finland Birth Cohort. Using our multiple-haplotype IBD cluster approach, we found an association with a genomic interval covering the PCSK9 gene in these data that is missed by standard single-marker association tests. Previously published studies confirm association of PCSK9 with low-density lipoprotein. Source code is available under the GNU Public License http://cs.au.dk/~qianyuxx/EMI/.

HapFABIA: Identification of very short segments of identity by descent characterized by rare variants in large sequencing data

Identity by descent (IBD) can be reliably detected for long shared DNA segments, which are found in related individuals. However, many studies contain cohorts of unrelated individuals that share only short IBD segments. New sequencing technologies facilitate identification of short IBD segments through rare variants, which convey more information on IBD than common variants. Current IBD detection methods, however, are not designed to use rare variants for the detection of short IBD segments. Short IBD segments reveal genetic structures at high resolution. Therefore, they can help to improve imputation and phasing, to increase genotyping accuracy for low-coverage sequencing and to increase the power of association studies. Since short IBD segments are further assumed to be old, they can shed light on the evolutionary history of humans. We propose HapFABIA, a computational method that applies biclustering to identify very short IBD segments characterized by rare variants. HapFABIA is designed to detect short IBD segments in genotype data that were obtained from next-generation sequencing, but can also be applied to DNA microarray data. Especially in next-generation sequencing data, HapFABIA exploits rare variants for IBD detection. HapFABIA significantly outperformed competing algorithms at detecting short IBD segments on artificial and simulated data with rare variants. HapFABIA identified 160 588 different short IBD segments characterized by rare variants with a median length of 23 kb (mean 24 kb) in data for chromosome 1 of the 1000 Genomes Project. These short IBD segments contain 752 000 single nucleotide variants (SNVs), which account for 39% of the rare variants and 23.5% of all variants. The vast majority—152 000 IBD segments—are shared by Africans, while only 19 000 and 11 000 are shared by Europeans and Asians, respectively. IBD segments that match the Denisova or the Neandertal genome are found significantly more often in Asians and Europeans but also, in some cases exclusively, in Africans. The lengths of IBD segments and their sharing between continental populations indicate that many short IBD segments from chromosome 1 existed before humans migrated out of Africa. Thus, rare variants that tag these short IBD segments predate human migration from Africa. The software package HapFABIA is available from Bioconductor. All data sets, result files and programs for data simulation, preprocessing and evaluation are supplied at http://www.bioinf.jku.at/research/short-IBD.

Detecting Identity by Descent and Estimating Genotype Error Rates in Sequence Data

Existing methods for identity by descent (IBD) segment detection were designed for SNP array data, not sequence data. Sequence data have a much higher density of genetic variants and a different allele frequency distribution, and can have higher genotype error rates. Consequently, best practices for IBD detection in SNP array data do not necessarily carry over to sequence data. We present a method, IBDseq, for detecting IBD segments in sequence data and a method, SEQERR, for estimating genotype error rates at low-frequency variants by using detected IBD. The IBDseq method estimates probabilities of genotypes observed with error for each pair of individuals under IBD and non-IBD models. The ratio of estimated probabilities under the two models gives a LOD score for IBD. We evaluate several IBD detection methods that are fast enough for application to sequence data (IBDseq, Beagle Refined IBD, PLINK, and GERMLINE) under multiple parameter settings, and we show that IBDseq achieves high power and accuracy for IBD detection in sequence data. The SEQERR method estimates genotype error rates by comparing observed and expected rates of pairs of homozygote and heterozygote genotypes at low-frequency variants in IBD segments. We demonstrate the accuracy of SEQERR in simulated data, and we apply the method to estimate genotype error rates in sequence data from the UK10K and 1000 Genomes projects.