zprime(imageHTS)
zprime()所属R语言包：imageHTS
Compute the Z'-factor quality score
计算Z要素的质量得分
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Compute the Z'-factor quality score.
计算Z因素的质量得分。
用法----------Usage----------
zprime(a, b, method=c('mahalanobis', 'robust', 'fixsd', 'original'))
参数----------Arguments----------
参数：a, b
Matrices of control features.
矩阵的控制功能。
参数：method
a character vector, indicating which method should be used to compute the Z'-factor. Default is mahalanobis. See Details.
字符向量，表示应使用哪种方法来计算的Z因素。默认mahalanobis。查看详细信息。
Details
详情----------Details----------
The Z'-factor is a popular metric measuring the separation of control features in high-throughput screens. The original paper describing the Z'-factor is Zhang, 1999, J Biomol Screen.
Z的因素是一个受欢迎的度量测量控制功能，在高通量筛选分离。原来的文件，说明的Z因素是张，1999年，歼BIOMOL屏幕。
Several univariate Z'-factor scores exist. The original Z'-factor from Zhang, 1999 is computed by Z' = 1 - 3*(sd(a)+sd(b))/abs(mean(a)-mean(b)). A more rigorous definition of the score, implemented by the method fixsd is given by Z' = 1 - 3*sqrt(var(a)+var(b))/abs(mean(a)-mean(b)), where the pooled standard deviation is computed by the square root of the sum of the control variances. A robust method, less sensitive to outliers, is computed by the relation Z' = 1-3*(mad(a)+mad(b))/abs(median(a)-median(b)) where the control dispersions are computed with the mad and the control locations with the median.
几个单因素Z因子得分存在。 original，1999年从张Z因素计算的Z = 1 - 3 *（SD（一）+ SD（B））/ ABS（（一）平均（b）项）。一个更严格的定义，实施的方法fixsd得分，由Z = 1 - 3 * SQRT（VAR（一）+ VAR（B））/ ABS（指：（一）平均（二）），其中汇集的标准偏差计算平方根的控制差异的总和。一个robust方法，不敏感的离群值，计算关系Z“= 1-3 *（狂（一）+狂（b）项）/ ABS（中位数（一）中位数（b）项）控制分散的计算中位数狂和控制的地点。
A multivariate extension of the Z'-factor score can be designed by linearly transforming the multivariate data to one dimension and computing the standard (here, fixsd) Z'-factor. It can be shown that the linear transform that maximizes the score is the LDA. Moreover, one can demonstrate that the resulting Z'-factor score is equivalent of computing Z' = 1 - 3/dMaha(mu_a, mu_b, Sigma_a + Sigma_b) where dMaha is the Mahalanobis distance.
可以设计一个多元扩展Z因子得分线性多元数据转化到一维和计算标准（在这里，fixsd）Z因素。它可以证明，最大限度地将比分是线性变换的LDA。此外，可以证明，由此产生的Z因子得分计算Z“= 1相当于 - 3/dMaha（mu_a，mu_b，Sigma_a + Sigma_b）的地方dMaha是马氏距离。
值----------Value----------
The Z'-factor, a numeric ranging from -infinity to 1.
Z的因素，数值范围从无穷大到1。
作者（S）----------Author(s)----------
Gregoire Pau, <a href="mailto:gregoire.pau@embl.de">gregoire.pau@embl.de</a>, 2010
参考文献----------References----------
Statistical Parameter for Use in Evaluation and Validation of High Throughput Screening Assays. J Biomol Screening, 1999.
参见----------See Also----------
readHTS
readHTS
举例----------Examples----------
## initialize imageHTS object using the local submorph screen[＃初始化imageHTS对象使用当地submorph屏幕。]
local = tempdir()
server = system.file('submorph', package='imageHTS')
x = parseImageConf('conf/imageconf.txt', localPath=local, serverURL=server)
x = configure(x, 'conf/description.txt', 'conf/plateconf.txt', 'conf/screenlog.txt')
## get profiles[＃得到型材]
profiles = readHTS(x, type='file', filename='data/profiles.tab', format='tab')
a = profiles[match(getUnames(x, content='rluc'), profiles$uname),]
b = profiles[match(getUnames(x, content='ubc'), profiles$uname),]
## compute Z'-factor scores on some features[＃计算某些功能Z因子得分]
ft = c('med.c.m.m.ss')
cat('Z\'-factor original=', zprime(a[,ft], b[,ft], 'original'), 'fixsd=', zprime(a[,ft], b[,ft], 'fixsd'), '\n')
## multivariate Z'-factor[＃多元因素Z]
ft = c('med.c.m.m.ss', 'med.n.h.m.ss', 'med.c.g.ec')
cat('Z\'-factor mahalanobis=', zprime(a[,ft], b[,ft], 'mahalanobis'), '\n')
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 22:17:35
