ITALICS(ITALICS)
ITALICS()所属R语言包：ITALICS
Affymetrix SNP chip normalization
Affymetrix公司的SNP芯片标准化
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Normalize and analyse Affymetrix SNP array 100K and 500K set (see the vignette)
标准化和分析Affymetrix公司的SNP阵列100K和500K集（见插曲）
用法----------Usage----------
ITALICS(quartetInfo, snpInfo, confidence=0.95, iteration=2,
formule="Smoothing+QuartetEffect+FL+I(FL^2)+I(FL^3)+GC+I(GC^2)+I(GC^3)", prc=0.3,
amplicon=2.1, deletion=-3.5, deltaN=0.15, forceGL=c(-0.2,0.2), param=c(d=2), nbsigma=1, ... )
参数----------Arguments----------
参数：quartetInfo
a data frame containing all the raw quartet intensities plus there GC content, fragment length, and Quartet effect
一个数据框包含所有原始四重奏强度加有GC含量片段长度，和四方的影响
参数：snpInfo
a data frame containing SNPs position along the genome and raw copy number
一个数据框包含沿基因组的原始拷贝数个SNP的位置
参数：confidence
The confidence interval. After the last bias estimation step, quartets outside this confidence interval are flagged. The lower confidence is, the more quartets will be flagged. See also the parameter prc.
置信区间。最后的偏差估计一步后，这个置信区间之外的四重奏标记。信心是较低的，更四重奏将被标记。又见参数中国。
参数：iteration
The number of iteration you d'like to do
你，喜欢做的迭代次数
参数：formule
A symbolic description of the term of the model. The default value of formule means that we want correct the observed quartetLogRatio using the estimated copy number (Smoothing), the Quartet Effect, the quartet Fragment Length (FL) and the quartet GC content.
任期模型的一个象征性的描述。默认值的方程式表示，我们要正确的估计拷贝数（平滑），四方的影响，四方片段长度（FL）和四方GC含量的观察quartetLogRatio使用。
参数：prc
prc is a frequence (between 0 and 1). After the final iteration of ITALICS, badly predicted probes are flagged (see also the parameter confidence). Only SNPs having more than prc of their probes non-flagged are kept for the final GLAD analysis. The higher prc is, the more SNPs are removed before the final GLAD analysis.
中国是一个频率（0和1之间）。最后一次迭代后斜体，不好预测探针标记（见参数信心）。唯一的SNPs超过中国探针非标记保留最终GLAD分析。较高的中国，更多的SNPs被删除前的最后GLAD分析。
参数：amplicon
see the amplicon parameter in the daglad function
看到在daglad功能的扩增参数
参数：deletion
see the deletion parameter in the daglad function
看到在删除的daglad功能参数
参数：deltaN
see the deltaN parameter in the daglad function
看到在daglad功能DELTAN参数
参数：forceGL
see the forceGL parameter in the daglad function
看到在daglad功能forceGL参数
参数：param
see the param parameter in the daglad function
看到在daglad功能参数参数
参数：nbsigma
see the nbsigma parameter in the daglad function
看到在daglad功能nbsigma参数
参数：...
Other daglad parameters.
其他daglad参数。
Details
详情----------Details----------
The function ITALICS implements the methodology which is described in the article : ITALICS: an algorithm for normalization and DNA copy number calling for Affymetrix SNP arrays (Rigaill et al., Bioinformatics Advance Access published on February 5, 2008).
功能ITALICS实现在文章中所描述的方法：斜体：标准化和Affymetrix公司的SNP阵列（。Rigaill等，生物信息学进展，2008年2月5日公布的访问）调用的DNA拷贝数的算法。
The principle of the ITALICS algorithm: ITALICS, is a normalization method that estimates both the biological and the non-relevant effects in an alternate and iterative way to accurately remove the non-relevant effects.
斜体算法的原则：斜体，是一个标准化的方法，估计生物和在备用的非相关影响和迭代的方式准确地消除非相关影响。
ITALICS deals with known systematic sources of variation such as the GC-content of the quartets, the PCR amplified fragment length and the GC-content of the PCR amplified fragment . It also takes into account the quartet effect which corresponds to the fact that some quartets systematically have a small intensity while others tend to have a high intensity. ITALICS is also able to correct spatial artifacts which sometimes arise on Affymetrix SNP arrays 100K and 500K set.
变异的来源，如四重奏，PCR扩增片段长度和GC含量的PCR扩增GC含量与已知的系统斜体。它也需要考虑到四方对应的事实，一些四重奏系统有一个小强度的效果，而其他人往往有一个高强度。斜体也是能够纠正有时出现在Affymetrix SNP芯片100K和500K集的空间文物。
值----------Value----------
Return an object of class profileCGH
返回类profileCGH对象
注意----------Note----------
People interested in tools dealing with array CGH analysis and DNA copy number analysis can
阵列比较基因组杂交分析和DNA拷贝数的分析与处理工具有兴趣的人可以
作者（S）----------Author(s)----------
Guillem Rigaill, <a href="mailto:italics@curie.fr">italics@curie.fr</a>.
源----------Source----------
Institut Curie, italics@curie.fr.
居里研究所，italics@curie.fr。
举例----------Examples----------
## Not run: [＃无法运行：]
## step to get the path of the HF0844_Hind.CEL file[＃步骤得到的HF0844_Hind.CEL文件的路径]
ITALICSDataPATH <- attr(as.environment(match("package:ITALICSData",search())),"path")
filename <- paste(ITALICSDataPATH,"/extdata/HF0844_Hind.CEL", sep="")
quartetEffectFile <- paste(ITALICSDataPATH,"/data/Hind.QuartetEffect.csv", sep="")
## load quartet effect[＃加载四方效果]
quartetEffect <- read.table(quartetEffectFile, sep=";", header=TRUE)
## load annotation using the pd.mapping50k.xba24 or pd.mapping50k.hind240 or pd.mapping250k.sty or pd.mapping250k.nsp package[＃加载标注使用的pd.mapping50k.xba24或pd.mapping50k.hind240或pd.mapping250k.sty或pd.mapping250k.nsp包]
headdetails <- readCelHeader(filename[1])
pkgname <- cleanPlatformName(headdetails[["chiptype"]])
snpInfo <- getSnpInfo(pkgname)
quartet <- getQuartet(pkgname, snpInfo)
## read cel files and format data[＃读取CEL文件和格式的数据。]
tmpExprs <- readCelIntensities(filename, indices=quartet$fid)
quartet$quartetInfo$quartetLogRatio <- readQuartetCopyNb(tmpExprs)
quartet$quartetInfo <- addInfo(quartet, quartetEffect)
snpInfo <- fromQuartetToSnp(cIntensity="quartetLogRatio", quartetInfo=quartet$quartetInfo, snpInfo=snpInfo)
## ITALICS normalization[＃斜体标准化]
profilSNPHind <- ITALICS(quartet$quartetInfo, snpInfo,
formule="Smoothing+QuartetEffect+FL+I(FL^2)+I(FL^3)+GC+I(GC^2)+I(GC^3)")
## plot the profile[＃绘制的轮廓。]
data(cytoband)
plotProfile(profilSNPHind, Smoothing="Smoothing", Bkp=TRUE, cytoband = cytoband)
## End(Not run)[＃结束（不运行）]
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注：
注1：为了方便大家学习，本文档为生物统计家园网机器人LoveR翻译而成，仅供个人R语言学习参考使用，生物统计家园保留版权。
注2：由于是机器人自动翻译，难免有不准确之处，使用时仔细对照中、英文内容进行反复理解，可以帮助R语言的学习。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-2-25 22:43:22
