IGG3: a tool to rapidly integrate large genotype datasets for whole-genome imputation and individual-level meta-analysis Export

@article{citeulike:4285138, abstract = {Summary: There is an urgent and increasing demand for integrating large genotype datasets across genome-wide association studies and HapMap project for whole-genome imputation and individual-level meta-analysis. A new algorithm was developed to efficiently merge raw genotypes across large datasets and implemented in the latest version of IGG, IGG3. In addition, IGG3 can integrate the latest phased and unphased HapMap genotypes and can flexibly generate complete sets of input files for six popular genotype imputation tools. We demonstrated the efficiency of IGG3 by simulation tests, which could rapidly merge genotypes in tens of thousands of large genotype chips (e.g. Affymetrix Genome-Wide Human SNP Array 6.0 and Illumina Human1m-duo) and in HapMap III project on an ordinary desktop computer. Availability: http://bioinfo.hku.hk/iggweb (version 3.0). Contacts: songy@hkucc.hku.hk; limx54@yahoo.com Supplementary information: Supplementary data are available at Bioinformatics online. 10.1093/bioinformatics/btp183}, author = {Li, Miao-Xin and Jiang, Lin and Kao, Patrick Y. and Sham, Pak-C and Song, You-Qiang}, citeulike-article-id = {4285138}, citeulike-linkout-0 = {http://dx.doi.org/10.1093/bioinformatics/btp183}, citeulike-linkout-1 = {http://bioinformatics.oxfordjournals.org/content/25/11/1449.abstract}, citeulike-linkout-2 = {http://bioinformatics.oxfordjournals.org/content/25/11/1449.full.pdf}, citeulike-linkout-3 = {http://view.ncbi.nlm.nih.gov/pubmed/19346322}, citeulike-linkout-4 = {http://www.hubmed.org/display.cgi?uids=19346322}, day = {1}, doi = {10.1093/bioinformatics/btp183}, issn = {1460-2059}, journal = {Bioinformatics}, keywords = {arrays, genotyping, snps}, month = {June}, number = {11}, pages = {1449--1450}, posted-at = {2009-04-07 19:50:39}, priority = {2}, title = {IGG3: a tool to rapidly integrate large genotype datasets for whole-genome imputation and individual-level meta-analysis}, url = {http://dx.doi.org/10.1093/bioinformatics/btp183}, volume = {25}, year = {2009} }

TY - JOUR ID - citeulike:4285138 L3 - citeulike-article-id:4285138 N2 - Summary: There is an urgent and increasing demand for integrating large genotype datasets across genome-wide association studies and HapMap project for whole-genome imputation and individual-level meta-analysis. A new algorithm was developed to efficiently merge raw genotypes across large datasets and implemented in the latest version of IGG, IGG3. In addition, IGG3 can integrate the latest phased and unphased HapMap genotypes and can flexibly generate complete sets of input files for six popular genotype imputation tools. We demonstrated the efficiency of IGG3 by simulation tests, which could rapidly merge genotypes in tens of thousands of large genotype chips (e.g. Affymetrix Genome-Wide Human SNP Array 6.0 and Illumina Human1m-duo) and in HapMap III project on an ordinary desktop computer. Availability: http://bioinfo.hku.hk/iggweb (version 3.0). Contacts: songy@hkucc.hku.hk; limx54@yahoo.com Supplementary information: Supplementary data are available at Bioinformatics online. 10.1093/bioinformatics/btp183 IS - 11 JF - Bioinformatics SN - 1460-2059 EP - 1450 TI - IGG3: a tool to rapidly integrate large genotype datasets for whole-genome imputation and individual-level meta-analysis VL - 25 SP - 1449 KW - arrays KW - genotyping KW - snps AU - Li, Miao-Xin AU - Jiang, Lin AU - Kao, Patrick AU - Sham, Pak-C AU - Song, You-Qiang PY - 2009/06/01/ UR - http://dx.doi.org/10.1093/bioinformatics/btp183 ER -