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**findhap.f90**
Find haplotypes and impute genotypes using multiple chip sets and sequence dataDownloads
Version 4 program, example files, and executable*(beta version — not quite ready for routine use on U.S. chip data, but performs better than version 3 for sequence data)*
Example data files for imputation study presented by VanRaden and Sun at the 2014 World Congress on Genetics Applied to Livestock Production
Files include actual pedigree, simulated true genotypes, simulated sequence reads, and imputed genotypes
This example used 500 reference bulls sequenced at 4× with 1% error and containing high-density SNPs; the 250 young bulls used to test imputation had only high-density SNPs
Other examples in the study can be generated by setting other options for programs findhap4, geno2seq, and genosimVersion 3 program, example files, and executableVersion 2 program, example files, and executable*(not maintained)*Inputs
genotypes.txt
Format: animal# chip# #SNPs genotypesSort by animal#, genotype codes are 0,1,2, and 5 = missingFor fixed length input, set chip# to 1 and missing genotypes to 5For variable length input, #SNPs and order must match chromosome.datachromosome.data
List of all SNPs used and which SNPs are on each chipSort by chromosome number and position within chromosomeX-specific chromosome last, after pseudo-autosomal "chromosome"Y-specific SNPs not supported yetpedigree.file
Format: sex  animal#  sire#  dam#  birthdate  animal ID  animal nameSort in ascending birth date orderfindhap.options
Program control file with user-defined optionssequences.readdepth*(version 4 only)*
Format: animal#  chip#  #SNPsRead counts for A and B alleles stored in 1-byte hexadecimal formatOutputs
hap.list
List of all haplotypes found in each segment0hap.found
Each animal's paternal and maternal haplotypes (2 lines/animal)hap.inherit
Tracks inheritance and crossovers for each parental chromosomehap.filled
Summarizes imputation quality for each animalcross.overs
Lists exact location of all detected crossoversallele.frequency
Estimated allele frequencies and missing rates for each SNPgenotypes.filled
Imputed genotypes with codes: 0 = BB, 1 = AB, 2 = AA, 3 = B_, 4 = A_, 5 = __Number of animals output may exceed input because of imputed damsRemaining missing alleles in codes 3, 4, and 5 can be set using allele frequencieshaplotypes.txt
Imputed haplotypes: SNP1 paternal maternal, SNP2 pat mat, etc., for each animalNo missing alleles, allowing genotypes to be formed simply as (pat + mat - 2)Version differences
4 vs. 3
Can input numbers of A and B allele reads from sequence dataIncreased memory and CPU because of likelihood ratio calculations3 vs. 2
Computing time reduced by using priors or imputing only new animalsFiles hap.list and hap.found output multiple lengths to use as priorsOptions file includes damout, listout, and errate for outputting imputed parents, outputting all steps or only the final step, and allowing error within haplotypesOption genout can output only best call (0,1,2) or just missing (0,1,2,5) in genotypes.filled2 vs. 1
Options file uses maxlen, minlen, and steps to divide long segment into shorter segmentsComputing time increases by number of steps used to get from maxlen to minlenPopulation and pedigree haplotyping in one loop vs. 2 separate loopsSearches for great-grandparent haplotypes, not just genotyped parents and grandparentsHigher accuracy and/or fewer high-density genotypes requiredReferences
2015
VanRaden, P.M., C. Sun, and J.R. O'Connell. Fast imputation using medium- or low-coverage sequence data. BMC Genet. 16:82.2014
VanRaden, P.M., and C. Sun. Fast imputation using medium- or low-coverage sequence data. Proc. 10th World Congr. Genet. Appl. Livest. Prod., 179.2013
VanRaden, P.M., D.J. Null, M. Sargolzaei, G.R. Wiggans, M.E. Tooker, J.B. Cole, T.S. Sonstegard, E.E. Connor, M. Winters, J.B.C.H.M. van Kaam, A. Valenti, B.J. Van Doormaal, M.A. Faust, and G.A. Doak. Genomic imputation and evaluation using high-density Holstein genotypes. J. Dairy Sci. 96:668–678.2011
VanRaden, P.M., J.R. O'Connell, G.R. Wiggans, and K.A. Weigel. Genomic evaluations with many more genotypes. Genet. Sel. Evol. 43:10.2010
VanRaden, P.M. Genomic evaluations with many more genotypes and phenotypes. Proc. 9th World Congr. Genet. Appl. Livest. Prod., Leipzig, Germany, Aug. 1–6, Comm. 27.VanRaden, P.M., J.R. O'Connell, G.R. Wiggans, and K.A. Weigel. Combining different marker densities in genomic evaluation. Interbull Bull. 42:113–118.License
Fortran package findhap.f90 is public domain and was developed with U.S. taxpayer funding. Accurate results are not guaranteed. Please report any bugs to paul.vanraden@usda.gov. You may modify, improve, use, and redistribute the code to anyone for any purpose. Or, you can ask Paul to make changes that could benefit U.S. evaluations and other users. **Paul VanRaden**Animal Genomics and Improvement LaboratoryAgricultural Research Service, USDA


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