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Before reading this tutorial, you might find it useful to spend a few minutes reading through the main [[Minimac]] documentation.  
 
Before reading this tutorial, you might find it useful to spend a few minutes reading through the main [[Minimac]] documentation.  
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== Should I use MaCH or minimac? ==
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The imputation quality of both approaches is comparable.
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If you are carrying out only an one-time imputation, using a relatively small reference panel (with <200 haplotypes) and focusing only on autosomes - then go with MaCH. If you are using a large reference panel, planning to re-impute your data as new reference panels become available or interested in X-chromosome imputation - then minimac is the right choice for you.
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As of June 2011, the 1000 Genomes Panel set of reference haplotypes includes >2000 haplotypes, and you are likely to be better off using [[minimac]].
      
== Getting Started ==
 
== Getting Started ==
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If you are planning to use imputation with the MetaboChip, you might find a list of SNPs whose order varies between NCBI genome build 36 and 37 convenient. Here it is: [http://www.sph.umich.edu/csg/cfuchsb/metab_order_changed.txt List of Metabochip SNPs Whose Order Changes With Build]
 
If you are planning to use imputation with the MetaboChip, you might find a list of SNPs whose order varies between NCBI genome build 36 and 37 convenient. Here it is: [http://www.sph.umich.edu/csg/cfuchsb/metab_order_changed.txt List of Metabochip SNPs Whose Order Changes With Build]
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Note: For the most recent reference panel in VCF format GWAS SNPs have to be in the chr:pos format e.g. 1:1000 (NOT rsxxxxx)
    
=== Quality Control ===
 
=== Quality Control ===
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=== Reference Haplotypes ===
 
=== Reference Haplotypes ===
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Reference haplotypes generated by the 1000 Genomes project and formatted so that they are ready for analysis are available from the [http://www.sph.umich.edu/csg/abecasis/MaCH/download/ MaCH download page]. In our hands, it is ideal to always use the most recent release since generation of additional sequence data, improvements in variant discovery, genotyping and haplotyping strategies typically result in noticeable improvements in data quality. When this page was written, the most recent release of 1000 Genomes project haplotypes was the [http://www.sph.umich.edu/csg/abecasis/MaCH/download/1000G-PhaseI-Interim.html Interim Phase I release], including 1094 individuals genotyped at >37 million autosomal sites.
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Reference haplotypes generated by the 1000 Genomes project and formatted so that they are ready for analysis are available from the [http://www.sph.umich.edu/csg/abecasis/MaCH/download/ MaCH download page]. In our hands, it is ideal to always use the most recent release since generation of additional sequence data, improvements in variant discovery, genotyping and haplotyping strategies typically result in noticeable improvements in data quality. When this page was written, the most recent release of 1000 Genomes project haplotypes was the [http://www.sph.umich.edu/csg/abecasis/MACH/download/1000G.2012-03-14.html Integrated Phase I release], including 1094 individuals genotyped at >40 million autosomal sites.
    
== Minimac Imputation ==
 
== Minimac Imputation ==
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