Changes between Version 11 and Version 12 of Impute2Pipeline


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Timestamp:
May 8, 2013 3:47:49 PM (5 years ago)
Author:
freerkvandijk
Comment:

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  • Impute2Pipeline

    v11 v12  
    1414
    1515All analysis jobs are generated using [http://www.molgenis.org/wiki/ComputeStart MOLGENIS Compute], more information about MOLGENIS Compute and the other analysis pipelines can be found here: https://github.com/molgenis/molgenis-pipelines
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     19== Paper ready summary ==
    1620
    17 == Paper ready summary ==
     21UNDER CONSTRUCTION
    1822
    1923You can use the following text in your paper:
    2024
    21 TODO. Including citations.
     25==== Summary ====
     26The study data was lifted over from human genome build 36 to build 37 using Plink^([#hn 1])^ and UCSC liftOver, followed by alignment to reference data and filtering on MAF larger than 1%, Hardy-Weinberg Equilibrium p-value of  1e-4 and a call rate higher than 0.95. Afterwards the study data was pre-phased per chromosome using SHAPEIT2 v.2.644^([#hn 2])^. Finally the imputation over genome chunks of 5Mb was performed using IMPUTE2 2.3.0^([#hn 3])^. Here we used Genome of the Netherlands release 4 (499 unrelated individuals)^([#hn 4])^ and 1000 Genomes phase1 integrated version 3 (1092 individuals)^([#hn 5])^ respectively as reference panel.
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     28We used MOLGENIS compute^([#hn 6])^ to implement the imputation pipeline, keep track of all analysis jobs and easily distribute all imputation chunks in parallel on our PBS compute cluster and the national life science grid. All pipelines are available as open source via http://www.molgenis.org/wiki/ComputeStart.
     29
     30==== Acknowledgements ====
     31We would like to thank The Target project (http://www.rug.nl/target) for providing the compute infrastructure used for imputation and the BigGrid/eBioGrid project (http://www.ebiogrid.nl) for sponsoring the imputation pipeline implementation.
     32
     33==== References ====
     341.      Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR, Bender D, Maller J, Sklar P, de Bakker PIW, Daly MJ & Sham PC (2007) PLINK: a toolset for whole-genome association and population-based linkage analysis. American Journal of Human Genetics, 81, Available: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1950838/
     352.     Delaneau O, Zagury J-F, Marchini J (2013) Improved whole-chromosome phasing for disease and population genetic studies. Nature methods 10: 5–6. Available: http://dx.doi.org/10.1038/nmeth.2307
     363.     Howie BN, Donnelly P, Marchini J (2009) A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS genetics 5: e1000529. Available: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2689936&tool=pmcentrez&rendertype=abstract
     374.      Placeholder for GoNL paper
     385.      The 100 Genomes Project Consortium (2012) An integrated map of genetic variation from 1,092 human genomes. Nature, 491. Available: http://www.nature.com/nature/journal/v491/n7422/full/nature11632.html
     396.      Byelas, H., Dijkstra, M., Neerincx, P., Van Dijk, F., Kanterakis, A., Deelen, P., & Swertz, M. (2013). Scaling bio-analyses from computational clusters to grids. IWSG 2013.
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    2244
    2345== Reference data ==