gene.similarity(BUS)
gene.similarity()所属R语言包:BUS
Calculate adjacency matrix for gene-gene interaction
计算基因 - 基因相互作用的邻接矩阵
译者:生物统计家园网 机器人LoveR
描述----------Description----------
To calculate an adjacency matrix for gene-gene interaction (using correlation/mutual information metric). For gene expression data with M genes and N experiments, the adjacency matrix is in size of MxM. It is optional to get a trimmed adjacency matrix according to the argument net.trim, i.e. mrnet, clr andaracne (from the package minet).
基因 - 基因相互作用(使用相关/互信息度量)来计算的邻接矩阵。与M基因和N实验的基因表达数据,邻接矩阵是在MXM大小。得到修剪的邻接矩阵根据的的说法net.trim,即mrnet,CLR andaracne(包MINET),它是可选的。
用法----------Usage----------
gene.similarity(EXP, measure, net.trim, na.replica = 50)
参数----------Arguments----------
参数:EXP
Gene expression data in form of a matrix. Row stands for genes and column for experiments.
基因表达数据矩阵形式。行代表基因和实验列。
参数:measure
Metric used to calculate similarity between genes: "corr" for correlation, "MI" for mutual information.
度量用于计算互信息的基因之间的相似:“更正”的相关性,“智”。
参数:net.trim
Method used to trim the adjacency matrix: "mrnet", "clr", "aracne" and "none". "mrnet" infers a network using the maximum relevance/minimum redundancy feature selection method; "clr" use the CLR algorithm; "aracne" applies the data processing inequality to all triplets of nodes in order to remove the least significant edge in each triplet. These options come from the package minet, and they are used only for mutual information. "none" indicates no trim operation. It should be chosen when correlation is considered.
方法来修剪的邻接矩阵:“mrnet”,“CLR”,“aracne”和“无”。推断“mrnet”网络使用的最大相关性/最小冗余特征选择方法;“CLR”使用CLR算法;的“aracne”适用于数据处理节点的所有三胞胎的不平等,以消除最显着优势每个三胞胎。这些选项来自包MINET,它们仅用于互信息。 “无”表示没有修剪操作。它被认为是相关时,应选择。
参数:na.replica
Times of replication for filling NANs in the impute method; default value is 50. The (smooth) bootstrapping approach is used to give an estimation to missing value in the data.
填写在归罪于方法NaN的;次复制的默认值是50。 (平滑)自举方法是用来给估计值在数据丢失。
值----------Value----------
An adjacency matrix in size of MxM with rows and columns both standing for genes. Element in row i and column j indicates the similarity between gene i and gene j.
MXM大小的邻接矩阵的行和列的两个基因的地位。行中的元素i和j列表示基因I和基因j之间的相似性。
作者(S)----------Author(s)----------
Yin Jin, Hesen Peng, Lei Wang, Raffaele Fronza, Yuanhua Liu and Christine Nardini
举例----------Examples----------
data(copasi)
mat=as.matrix(copasi)[1:10,]
rownames(mat)<-paste("G",1:nrow(mat), sep="")
res<-gene.similarity(mat,measure="corr",net.trim="none")
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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