MaCH: 1000 Genomes Imputation Cookbook - Revision history

Goncalo at 07:08, 28 July 2011

2011-07-28T07:08:24Z

← Older revision		Revision as of 07:08, 28 July 2011
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	This page documents how to impute 1000 Genome SNPs using MaCH.		This page documents how to impute 1000 Genome SNPs using MaCH. It will almost always be more efficient to use [[Minimac]] to carry out imputation using large reference panels, such as the 1000 Genomes Project data. So, you are probably better off looking at the [[Minimac: 1000 Genomes Imputation Cookbook]].

	== Getting Started ==		== Getting Started ==
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	Within each file, markers should be stored by chromosome position. Alleles should be stored in the forward strand and can be encoded as 'A', 'C', 'G' or 'T' (there is no need to use numeric identifiers for each allele).		Within each file, markers should be stored by chromosome position. Alleles should be stored in the forward strand and can be encoded as 'A', 'C', 'G' or 'T' (there is no need to use numeric identifiers for each allele).

	The 1000 Genome pilot project genotypes use NCBI Build 36.		The 1000 Genome pilot project genotypes use NCBI Build 36; more recent releases use NCBI Build 37.

	=== Reference Haplotypes ===		=== Reference Haplotypes ===

	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/~~1000G-2010-06.html~~ MaCH download page]. The most recent set of haplotypes ~~were generated~~ in ~~June 2010 by combining~~ genotype ~~calls generated at the Broad~~, ~~Sanger and the University~~ of ~~Michigan. In our hands~~, ~~this June 2010 release~~ is ~~substantially~~ better ~~than previous~~ 1000 ~~Genome~~ Project ~~genotype call sets~~.		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]. The most recent set of haplotypes is usually available from the MaCH download page. Improvements in genotype calling and haplotyping methods, together with generation of progressively larger amounts of sequence data mean that, typically, it is better to use the most recent set of 1000 Genomes Project Haplotypes.

	== Estimating Model Parameters ==		== Estimating Model Parameters ==
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	== Quality Filtering ==		== Quality Filtering ==

	For 1000 Genome ~~SNPs~~, we ~~currently recommend~~ that any markers with estimated r<sup>2</sup> of <0.5 should be treated with caution. This is a bit more conservative than the threshold of 0.3 we ~~recommend~~ for HapMap; but 1000 Genome ~~SNP genotypes are~~ also (as of June 2010) of lower quality.		For the original 1000 Genome SNP sets, we typically recommended that any markers with estimated r<sup>2</sup> of <0.5 should be treated with caution. This is a bit more conservative than the threshold of 0.3 we recommended for HapMap; but early 1000 Genome Project haplotype sets were also (as of June 2010) of lower quality. In current iterations of the project data, it should be safe to use a less conservative r<sup>2</sup> cut-off.

Cfuchsb at 13:31, 7 October 2010

2010-10-07T13:31:48Z

← Older revision		Revision as of 13:31, 7 October 2010
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	=== Reference Haplotypes ===		=== Reference Haplotypes ===

	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/1000G-2010-03.html MaCH download page]. The most recent set of haplotypes were generated in ~~March~~ 2010 by combining genotype calls generated at the Broad, Sanger and the University of Michigan. In our hands, this ~~March~~ 2010 release is substantially better than previous 1000 Genome Project genotype call sets.		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/1000G-2010-06.html MaCH download page]. The most recent set of haplotypes were generated in June 2010 by combining genotype calls generated at the Broad, Sanger and the University of Michigan. In our hands, this June 2010 release is substantially better than previous 1000 Genome Project genotype call sets.

	== Estimating Model Parameters ==		== Estimating Model Parameters ==
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	== Quality Filtering ==		== Quality Filtering ==

	For 1000 Genome SNPs, we currently recommend that any markers with estimated r<sup>2</sup> of <0.5 should be treated with caution. This is a bit more conservative than the threshold of 0.3 we recommend for HapMap; but 1000 Genome SNP genotypes are also (as of ~~March~~ 2010) of lower quality.		For 1000 Genome SNPs, we currently recommend that any markers with estimated r<sup>2</sup> of <0.5 should be treated with caution. This is a bit more conservative than the threshold of 0.3 we recommend for HapMap; but 1000 Genome SNP genotypes are also (as of June 2010) of lower quality.

Goncalo: /* Selecting a Subset of Samples */

2010-06-04T11:52:26Z

Selecting a Subset of Samples

← Older revision		Revision as of 11:52, 4 June 2010
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	SAMPLE 200 PERSONS TO chr1.rand200.ped		SAMPLE 200 PERSONS TO chr1.rand200.ped

	QUIT		QUIT
	EOF		EOF
	</source>		</source>

Goncalo: /* Selecting a Subset of Samples */

2010-06-04T11:52:14Z

Selecting a Subset of Samples

← Older revision		Revision as of 11:52, 4 June 2010
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	Optionally, you can add the <code>--compact</code> option to the end of the command line to reduce memory use.		Optionally, you can add the <code>--compact</code> option to the end of the command line to reduce memory use.

	If you'd like to play it safe and sample 200 individuals at random, you could use [[PedScript] and a series of command similar to this one:		If you'd like to play it safe and sample 200 individuals at random, you could use [[PedScript]] and a series of command similar to this one:

	<source lang="text">		<source lang="text">

Goncalo: /* Imputation */

2010-06-04T11:17:31Z

Imputation

← Older revision		Revision as of 11:17, 4 June 2010
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	end		end
	</source>		</source>

			== Quality Filtering ==

			For 1000 Genome SNPs, we currently recommend that any markers with estimated r<sup>2</sup> of <0.5 should be treated with caution. This is a bit more conservative than the threshold of 0.3 we recommend for HapMap; but 1000 Genome SNP genotypes are also (as of March 2010) of lower quality.

Goncalo: /* Selecting a Subset of Samples */

2010-06-04T11:13:39Z

Selecting a Subset of Samples

@@ Line 69: / Line 69: @@
 EOF
-      runon mach -d chr$chr.rand200.dat -p chr$chr.rand200.ped -s CEU.1000G/chr$chr.snps -h CEU.1000G/chr$chr.hap \
+      runon -m 4096 mach -d chr$chr.rand200.dat -p chr$chr.rand200.ped -s CEU.1000G/chr$chr.snps -h CEU.1000G/chr$chr.hap \
-                 --greedy -r 100 -o chr$chr.parameters >& chr$chr.model.log &
+                        --greedy -r 100 -o chr$chr.parameters --compact >& chr$chr.model.log &
     end
 </source>

Goncalo: /* Estimating Model Parameters */

2010-06-04T11:08:46Z

Estimating Model Parameters

← Older revision		Revision as of 11:08, 4 June 2010
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	The first step for genotype imputation analyses using MaCH is to build a model that relates your dataset to a reference set of haplotypes. This model will include information on the length of haplotype stretches shared between your sample and the reference panel (in a ''.rec'' file) and information on the similarity of marker genotypes between your sample and the reference panel (in a ''.err'' file). The contents of the second file reflect the combined effects of genotyping error and differences in genotyping assays between the two samples.		The first step for genotype imputation analyses using MaCH is to build a model that relates your dataset to a reference set of haplotypes. This model will include information on the length of haplotype stretches shared between your sample and the reference panel (in a ''.rec'' file) and information on the similarity of marker genotypes between your sample and the reference panel (in a ''.err'' file). The contents of the second file reflect the combined effects of genotyping error and differences in genotyping assays between the two samples.

			In our view, MaCH's ability to estimate these parameters makes it especially robust to problems in genotyping, differences in genotyping assays and in the ability to adjust to varying degrees of similarity between the sample being imputed and a reference panel.

			=== Selecting a Subset of Samples ===

			Using all availalble samples to estimate model parameters can be quite time consuming and is typically not necessary. Instead, we recommend that you select a set of 200 samples to use in this step of analysis. If you are not worried about batch effects, you could just take the first 200 samples in your pedigree file, for example:

			head -200 chr1.ped > chr1.first200.ped

			And then run mach as:

			mach -d chr1.dat -p chr1.first200.ped -s CEU.1000G/chr1.snps -h CEU.1000G/chr1.hap --greedy -r 100 -o chr1.parameters

			Optionally, you can add the <code>--compact</code> option to the end of the command line to reduce memory use.

			If you'd like to play it safe and sample 200 individuals at random, you could use [[PedScript] and a series of command similar to this one:

			<source lang="text">
			pedscript << EOF
			READ DAT chr1.dat
			READ PED chr1.ped

			NUKE
			TRIM

			WRITE DAT chr1.rand200.dat
			SAMPLE 200 PERSONS TO chr1.rand200.ped

			QUIT
			EOF
			</source>

			Then, run mach just as before:

			mach -d chr1.rand200.dat -p chr1.rand200.ped -s CEU.1000G/chr1.snps -h CEU.1000G/chr1.hap --greedy -r 100 -o chr1.parameters

			You can decide on the exact number of samples to use for this analysis ... A number of between 100-500 individuals should be plenty. On a compute cluster, you should be able to run this step for all chromosomes in parallel; the exact syntax will depend on your cluster. In ours, we'd try something like:

			<source lang="text">
			foreach chr (`seq 1 22`)

			pedscript << EOF
			READ DAT chr$chr.dat
			READ PED chr$chr.ped
			NUKE
			TRIM
			WRITE DAT chr$chr.rand200.dat
			SAMPLE 200 PERSONS TO chr$chr.rand200.ped
			QUIT
			EOF

			runon mach -d chr$chr.rand200.dat -p chr$chr.rand200.ped -s CEU.1000G/chr$chr.snps -h CEU.1000G/chr$chr.hap \
			--greedy -r 100 -o chr$chr.parameters >& chr$chr.model.log &

			end
			</source>

Goncalo: /* Estimating Model Parameters */

2010-06-04T10:50:25Z

Estimating Model Parameters

← Older revision		Revision as of 10:50, 4 June 2010
Line 16:		Line 16:

	== Estimating Model Parameters ==		== Estimating Model Parameters ==

			The first step for genotype imputation analyses using MaCH is to build a model that relates your dataset to a reference set of haplotypes. This model will include information on the length of haplotype stretches shared between your sample and the reference panel (in a ''.rec'' file) and information on the similarity of marker genotypes between your sample and the reference panel (in a ''.err'' file). The contents of the second file reflect the combined effects of genotyping error and differences in genotyping assays between the two samples.

Goncalo: /* Reference Haplotypes */

2010-06-04T10:47:34Z

Reference Haplotypes

← Older revision		Revision as of 10:47, 4 June 2010
Line 13:		Line 13:
	=== Reference Haplotypes ===		=== Reference Haplotypes ===

	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]. The most recent set of haplotypes were generated in March 2010 by combining genotype calls generated at the Broad, Sanger and the University of Michigan. In our hands, this March 2010 release is substantially better than previous 1000 Genome Project genotype call sets.		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/1000G-2010-03.html MaCH download page]. The most recent set of haplotypes were generated in March 2010 by combining genotype calls generated at the Broad, Sanger and the University of Michigan. In our hands, this March 2010 release is substantially better than previous 1000 Genome Project genotype call sets.

	== Estimating Model Parameters ==		== Estimating Model Parameters ==

Goncalo: /* Reference Haplotypes */

2010-06-04T10:45:29Z

Reference Haplotypes

← Older revision		Revision as of 10:45, 4 June 2010
Line 13:		Line 13:
	=== Reference Haplotypes ===		=== Reference Haplotypes ===

	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]. The most recent set of haplotypes were generated in March 2010 by combining genotype calls generated at the Broad, Sanger and the University of Michigan. In our hands, this March 2010 release is substantially better than previous 1000 Genome Project genotype call sets.		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]. The most recent set of haplotypes were generated in March 2010 by combining genotype calls generated at the Broad, Sanger and the University of Michigan. In our hands, this March 2010 release is substantially better than previous 1000 Genome Project genotype call sets.

	== Estimating Model Parameters ==		== Estimating Model Parameters ==