findhap.f90	Find haplotypes and impute genotypes using multiple chip sets and sequence data
Downloads	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 genosim
	Version 3 program, example files, and executable
	Version 2 program, example files, and executable (not maintained)
Inputs	genotypes.txt	Format: animal# chip# #SNPs genotypes Sort by animal#, genotype codes are 0,1,2, and 5 = missing For fixed length input, set chip# to 1 and missing genotypes to 5 For variable length input, #SNPs and order must match chromosome.data
	chromosome.data	List of all SNPs used and which SNPs are on each chip Sort by chromosome number and position within chromosome X-specific chromosome last, after pseudo-autosomal "chromosome" Y-specific SNPs not supported yet
	pedigree.file	Format: sex  animal#  sire#  dam#  birthdate  animal ID  animal name Sort in ascending birth date order
	findhap.options	Program control file with user-defined options
	sequences.readdepth (version 4 only)	Format: animal#  chip#  #SNPs Read counts for A and B alleles stored in 1-byte hexadecimal format
Outputs	hap.list	List of all haplotypes found in each segment0
	hap.found	Each animal's paternal and maternal haplotypes (2 lines/animal)
	hap.inherit	Tracks inheritance and crossovers for each parental chromosome
	hap.filled	Summarizes imputation quality for each animal
	cross.overs	Lists exact location of all detected crossovers
	allele.frequency	Estimated allele frequencies and missing rates for each SNP
	genotypes.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 dams Remaining missing alleles in codes 3, 4, and 5 can be set using allele frequencies
	haplotypes.txt	Imputed haplotypes: SNP1 paternal maternal, SNP2 pat mat, etc., for each animal No 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 data Increased memory and CPU because of likelihood ratio calculations
	3 vs. 2	Computing time reduced by using priors or imputing only new animals Files hap.list and hap.found output multiple lengths to use as priors Options file includes damout, listout, and errate for outputting imputed parents, outputting all steps or only the final step, and allowing error within haplotypes Option genout can output only best call (0,1,2) or just missing (0,1,2,5) in genotypes.filled
	2 vs. 1	Options file uses maxlen, minlen, and steps to divide long segment into shorter segments Computing time increases by number of steps used to get from maxlen to minlen Population and pedigree haplotyping in one loop vs. 2 separate loops Searches for great-grandparent haplotypes, not just genotyped parents and grandparents Higher accuracy and/or fewer high-density genotypes required
References	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. You may modify, improve, use, and redistribute the code to anyone for any purpose.