SNPchip: R classes and methods for SNP array data. Export

@article{citeulike:1030354, abstract = {High-density single nucleotide polymorphism microarrays (SNP chips) provide information on a subject's genome, such as copy number and genotype (heterozygosity/homozygosity) at a SNP. While fluorescence in situ hybridization and karyotyping reveal many abnormalities, SNP chips provide a higher resolution map of the human genome that can be used to detect, e.g., aneuploidies, microdeletions, microduplications and loss of heterozygosity (LOH). As a variety of diseases are linked to such chromosomal abnormalities, SNP chips promise new insights for these diseases by aiding in the discovery of such regions, and may suggest targets for intervention. The R package SNPchip contains classes and methods useful for storing, visualizing and analyzing high density SNP data. Originally developed from the SNPscan web-tool, SNPchip utilizes S4 classes and extends other open source R tools available at Bioconductor. This has numerous advantages, including the ability to build statistical models for SNP-level data that operate on instances of the class, and to communicate with other R packages that add additional functionality. AVAILABILITY: The package is available from the Bioconductor web page at www.bioconductor.org. SUPPLEMENTARY INFORMATION: The supplementary material as described in this article (case studies, installation guidelines and R code) is available from http://biostat.jhsph.edu/\~{}iruczins/publications/sm/}, address = {Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland 21205.}, author = {Scharpf, Robert B. and Ting, Jason C. and Pevsner, Jonathan and Ruczinski, Ingo}, citeulike-article-id = {1030354}, citeulike-linkout-0 = {http://dx.doi.org/10.1093/bioinformatics/btl638}, citeulike-linkout-1 = {http://bioinformatics.oxfordjournals.org/cgi/content/abstract/23/5/627}, citeulike-linkout-2 = {http://view.ncbi.nlm.nih.gov/pubmed/17204461}, citeulike-linkout-3 = {http://www.hubmed.org/display.cgi?uids=17204461}, day = {1}, doi = {10.1093/bioinformatics/btl638}, issn = {1460-2059}, journal = {Bioinformatics (Oxford, England)}, keywords = {rclassesmethods, snp}, month = {March}, number = {5}, pages = {627--628}, posted-at = {2007-05-02 15:06:17}, priority = {0}, title = {SNPchip: R classes and methods for SNP array data.}, url = {http://dx.doi.org/10.1093/bioinformatics/btl638}, volume = {23}, year = {2007} }

TY - JOUR ID - citeulike:1030354 L3 - citeulike-article-id:1030354 N2 - High-density single nucleotide polymorphism microarrays (SNP chips) provide information on a subject's genome, such as copy number and genotype (heterozygosity/homozygosity) at a SNP. While fluorescence in situ hybridization and karyotyping reveal many abnormalities, SNP chips provide a higher resolution map of the human genome that can be used to detect, e.g., aneuploidies, microdeletions, microduplications and loss of heterozygosity (LOH). As a variety of diseases are linked to such chromosomal abnormalities, SNP chips promise new insights for these diseases by aiding in the discovery of such regions, and may suggest targets for intervention. The R package SNPchip contains classes and methods useful for storing, visualizing and analyzing high density SNP data. Originally developed from the SNPscan web-tool, SNPchip utilizes S4 classes and extends other open source R tools available at Bioconductor. This has numerous advantages, including the ability to build statistical models for SNP-level data that operate on instances of the class, and to communicate with other R packages that add additional functionality. AVAILABILITY: The package is available from the Bioconductor web page at www.bioconductor.org. SUPPLEMENTARY INFORMATION: The supplementary material as described in this article (case studies, installation guidelines and R code) is available from http://biostat.jhsph.edu/~iruczins/publications/sm/ IS - 5 JF - Bioinformatics (Oxford, England) SN - 1460-2059 AD - Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland 21205. EP - 628 TI - SNPchip: R classes and methods for SNP array data. VL - 23 SP - 627 KW - rclassesmethods KW - snp AU - Scharpf, Robert AU - Ting, Jason AU - Pevsner, Jonathan AU - Ruczinski, Ingo PY - 2007/03/01/ UR - http://dx.doi.org/10.1093/bioinformatics/btl638 ER -