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'''MaCH''' (MArkov Chain Haplotyping), mostly known as a software for genotype imputation, is a Hidden Markov Model (HMM) based haplotyper that reconstructs haplotypes from genotypes of unrelated individuals. Three primary utilities of MaCH are (1) to resolve haplotypes from diploid genotypes; (2) impute missing genotypes; and (3) perform disease mapping analysis.
[http://www.sph.umich.edu/csg/yli/mach/ '''MaCH'''] (MArkov Chain Haplotyping), mostly known as a software for genotype imputation, is a Hidden Markov Model (HMM) based haplotyper that reconstructs haplotypes from genotypes of unrelated individuals. Three primary utilities of MaCH are (1) to resolve haplotypes from diploid genotypes; (2) impute missing genotypes; and (3) perform disease mapping analysis.
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== FAQ ==
== FAQ ==
'''Q: Why and how to perform a 2-step imputation?'''<br>
'''Q: Why and how to perform a 2-step imputation?'''<br>
A: When one has a large number of individuals (>1000), we recommend a 2-step imputation to speed up. <br>
A: When one has a large number of individuals (>1000), we recommend a 2-step imputation to speed up. <br>
A 2-step imputation contains the following 2 steps:<br>
A 2-step imputation contains the following 2 steps:<br>
(step 1) a representative subset of >= 200 unrelated individuals are used to calibrate model parameters; and<br> (step 2) actual genotype imputation is performed for every person using parameters inferred in step 1. <br>
(step 1) a representative subset of >= 200 unrelated individuals are used to calibrate model parameters; and<br> (step 2) actual genotype imputation is performed for every person using parameters inferred in step 1. <br>
Example command lines for a 2-step imputation:<br>
mach1 -d sample.dat -p subset.ped -s chr20.snps -h chr20.hap --compact --greedy --autoFlip -r 100 -o par_infer > mach.infer.log
mach1 -d sample.dat -p subset.ped -s chr20.snps -h chr20.hap --compact --greedy --autoFlip -r 100 -o par_infer > mach.infer.log
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mach1 -d sample.dat -p sample.ped -s chr20.snps -h chr20.hap --compact --greedy --autoFlip <br>
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mach1 -d sample.dat -p sample.ped -s chr20.snps -h chr20.hap --compact --greedy --autoFlip
--errorMap par_infer.erate --crossoverMap par_infer.rec --mle --mldetails > mach.imp.log
'''Q: Where can I find combined HapMap reference files? '''<br> A: http://www.sph.umich.edu/csg/yli/mach/download/HapMap-r21.html <br><br>
'''Q: Where can I find combined HapMap reference files? '''<br> A: http://www.sph.umich.edu/csg/yli/mach/download/HapMap-r21.html <br><br>
The combined files should look like:<br> '''comb.ped'''<br> r1 r1 0 0 1 A/C C/C G/G G/A A/A<br> 1 1 0 0 1 A/A ./. ./. G/G ./.
The combined files should look like:<br> '''comb.ped'''<br> r1 r1 0 0 1 A/C C/C G/G G/A A/A<br> 1 1 0 0 1 A/A ./. ./. G/G ./.
'''comb.dat'''<br> M SNP1<br> M SNP2<br> M SNP3<br> M SNP4<br> M SNP5<br>
'''comb.dat'''<br> M SNP1<br> M SNP2<br> M SNP3<br> M SNP4<br> M SNP5<br>
== Examples ==
== Examples ==
