1 - 15 of 15 results


A method for estimating inbreeding identity by descent (IBD) tracts from low coverage next-generation sequencing data. Contrary to other methods that use genotype data, the one presented here uses genotype likelihoods to take the uncertainty of the data into account. We evaluate its performance through both simulated and real data analyses. When compared to genotype-calling-based methods, the improvement in accuracy when estimating IBD tracts and individual inbreeding coefficients is considerable for sequencing depths < 3×.

XIBD / X chromosome Identity by Descent

Performs pairwise relatedness mapping on the X chromosome using dense single nucleotide polymorphism (SNP) data from either SNP chips or next generation sequencing data. It correctly accounts for the difference in chromosomal numbers between males and females and estimates global relatedness as well as regions of the genome that are identical by descent (IBD). XIBD also generates novel graphical summaries of all pairwise IBD tracts for a cohort making it very useful for disease locus mapping.

FISHR / Find IBD Shared Haplotypes Rapidly

Detects IBD segments and estimates their endpoints using an algorithm that is fast enough to be deployed on the very large whole-genome SNP datasets. We compared the performance of FISHR to three leading IBD segment detection programs: GERMLINE, refinedIBD, and HaploScore. Using simulated and real genomic sequence data, we show that FISHR is slightly more accurate than all programs at detecting long (greater than 3 cM) IBD segments but slightly less accurate than refinedIBD at detecting short (1 cM) IBD segments. Moreover, FISHR outperforms all programs in determining the true endpoints of IBD segments, which is important for several reasons. FISHR takes two to four times longer than GERMLINE to run, whereas both GERMLINE and FISHR were orders of magnitude faster than refinedIBD and HaploScore. Overall, FISHR provides accurate IBD detection in unrelated individuals and is computationally efficient enough to be utilized on large SNP datasets greater than 20,000 individuals.


A tool for detecting identity-by-descent (IBD) tracts between pairs of genomic sequences. This method builds on a recent demographic inference method based on the coalescent with recombination, and is able to incorporate demographic information as a prior. Simulation study shows that diCal-IBD has significantly higher recall and precision than that of existing single-nucleotide polymorphism-based IBD detection methods, while retaining reasonable accuracy for IBD tracts as small as 0.1 cM.


Allows breeders and researchers to monitor changes in the genetic variability and structure of the populations with limited cost of preparing datasets. ENDOG provides a number of features that may be interest to teachers and students to develop an in-depth understanding of important statistical concepts and procedures for population genetic analysis. It enables to handle very large data files and is particularly designed to the analysis of diploid populations in which no selfing is possible.

PEDIBD / PEDigree Identical-By-Descent

Reconstructs haplotypes in large families allowing many ungenotyped individuals. PEDIBD consists of three major steps: pairwise identical-by-descent (IBD) inference, global IBD reconstruction, and haplotype restoring. By reconstructing the global IBD of a family from pairwise IBD and then restoring the haplotypes based on the inferred IBD, this method can scale to large pedigrees, and more importantly it can handle families with missing members. This method is based on linear systems, it exhausts all available constraints imposed by global IBD and genotypes, thus maximizes the usage of information in a family. Comparing with other methods, our PEDIBD has a much higher power to recover allelic phases in families with many missing members.