SNPchip: R classes and methods for SNP array data.
SNPchip: R classes and methods for SNP array data.
复制标题
SNPchip：SNP 数组数据的 R 类和方法。
DOI：
10.1093/bioinformatics/btl638
复制
发表时间：
2007
期刊：
影响因子：
--
通讯作者：
Ruczinski,Ingo
中科院分区：
文献类型：
--
作者：
Scharpf,RobertB;Ting,JasonC;Pevsner,Jonathan;Ruczinski,Ingo
摘要：高密度单核苷酸多态性微阵列（SNP芯片）提供受试者基因组的信息，如SNP的拷贝数和基因型（杂合性/纯合性）。虽然荧光原位杂交和核型分析揭示了许多异常，但SNP芯片提供了更高分辨率的人类基因组图谱，可用于检测，例如，非整倍性、微缺失、微重复和杂合性缺失（洛杂合性缺失）。由于各种疾病都与这种染色体异常有关，SNP芯片通过帮助发现这些区域，为这些疾病提供了新的见解，并可能提出干预目标。R packageSNPchip包含用于存储、可视化和分析高密度SNP数据的类和方法。SNPchipulizes S4类，并扩展了Bioconductor提供的其他开源R工具。这有很多优点，包括能够为SNP级别的数据构建统计模型，这些模型在类的实例上运行，以及能够与其他添加额外功能的R包进行通信。可用性：该包可从Bioconductor的网页获得，网址为www.bioconductor. org联系方式：ingo@jhu. edu补充信息：本文中描述的补充材料（案例研究、安装指南和R代码）可从http://biostat.jhsph.edu/~iruczins/publications/sm/获得。
Summary: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 fluorescencein situhybridization 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 packageSNPchipcontains classes and methods useful for storing, visualizing and analyzing high density SNP data. Originally developed from the SNPscan web-tool,SNPchiputilizes 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.orgContact:ingo@jhu.eduSupplementary 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/