distances(GeneExpressionSignature)
distances()所属R语言包：GeneExpressionSignature
Compute pairwise distances between samples
计算成对样本之间距离
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Compute pairwise distances between sample according to their (Prototype Ranked List) PRL, get a n-n distance matrix as the assay data of the result , n is the length of PRL.
（原型排名名单）泌乳素计算样本之间的成对距离，得到的检测数据结果1 NN距离矩阵，N是泌乳素长度。
用法----------Usage----------
distances(aggregateSet, qlen)
参数----------Arguments----------
参数：aggregateSet
an ExpressionSet object. The assay data represents the PRLs of the samples, each column represents one PRL. The number of column of this argument must be greater than 1, oherwise, this function is not meaningful.
一个ExpressionSet的对象。检测数据代表样品PRLs，每一列代表一个泌乳素。这一论点的列数必须大于1，oherwise，这个功能是没有意义的。
参数：qlen
the length of "gene signature". In order to compute pairwise distances among samples, genes lists are ranked according to the gene expression ratio (fold change). And the "gene signature" includes the most up-regulated genes (near the top of the list) and the most down-regulated genes (near the bottom of the list).
“基因签名”的长度。以计算样本间成对距离，基因名单排名根据基因表达比率（倍的变化）。和“基因签名”，包括大部分上调基因（列表的顶部附近）和下调基因（靠近列表的底部）。
Details
详情----------Details----------
Once the PRL obtained for each sample, the distances between samples are calculated base on gene signature, including the expression of genes that seemed to consistently vary in response to the across different experimental conditions (e.g., different cell lines and different dosages).
一旦泌乳素获得每个样品，样本之间的距离计算基因签名的基础上，包括表达的基因，似乎始终在回应而有所改变，在不同的实验条件下（例如，不同的单元系和不同剂量）。
值----------Value----------
参数：ES
an ExpressionSet, assay data is the enrichment score matrix
ExpressionSet，实验数据是浓缩的得分矩阵
参数：DS
an ExpressionSet, assay data is the distance matrix, the maximum distance is more sensitive to weak similarities, providing a lower precision but a larger recall.
ExpressionSet，实验数据的距离矩阵，最大距离是比较敏感的弱相似，提供了一个较低的精度，但更大的召回。
参见----------See Also----------
aggregate
aggregate
举例----------Examples----------
## create an instance ExpressionSet[＃创建一个实例ExpressionSet]
library(Biobase)
PRLs=as.matrix(read.table(system.file("extdata/example_PRLs.txt",package="GeneExpressionSignature")))
states=read.table(system.file("extdata/example_states.txt",package="GeneExpressionSignature"))
rownames(states)=colnames(PRLs)
phenodata=new("AnnotatedDataFrame",data = states)
exampleSet=new("ExpressionSet",exprs=PRLs,phenoData=phenodata)
## aggregate the exampleSet [＃聚合的exampleSet]
PRL=aggregate(exampleSet)
## compute distances from aggregated matrix[＃计算距离从聚合矩阵]
d=distances(PRL,250)
enrichmentscore=d[[1]]
distance=d[[2]]
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 18:43:57
