selectGeneSets(sigPathway)
selectGeneSets()所属R语言包:sigPathway
Select gene sets to be analyzed in pathway analysis
选择途径分析分析基因集
译者:生物统计家园网 机器人LoveR
描述----------Description----------
Selects gene sets to be analyzed in pathway analysis based on minimum and maximum number of probe sets to consider per pathway.
基因选择设置在途径分析的基础上最大和最小的探针数量分析的设置要考虑每通路。
用法----------Usage----------
selectGeneSets(G, probeID, minNPS = 20, maxNPS = 500)
参数----------Arguments----------
参数:G
a list containing the source, title, and probe sets associated with each curated pathway
列表包含源代码,标题和探针集相关联的每个策划途径
参数:probeID
a character vector containing the names of probe sets associated with a matrix of expression values
探针组与矩阵表达式的值关联的名称字符向量
参数:minNPS
an integer specifying the minimum number of probe sets in probeID that should be in a gene set
一个整数,指定最低数量的探针设置在probeID应该是在基因组
参数:maxNPS
an integer specifying the maximum number of probe sets in probeID that should be in a gene set
一个整数,指定的最大数量的探针设置在probeID应该是在基因组
Details
详情----------Details----------
This function selects the appropriate pathways from a large, curated list based on the minimum and maximum number of probe sets that should be considered in a gene set. It creates three vectors: nprobesV and indexV representing a sparse indicator matrix and indGused indicating which gene sets were selected from G.
此功能选择适当的途径,从一个大的,策划根据探针集的最低和最高数量,应考虑在基因组的列表。它创建三个向量:nprobesV和indexV较稀疏的指标矩阵和indGused表明基因组从G选择。
值----------Value----------
A list containing
一份列表,列出
参数:nprobesV
an integer vector indicating the number of probe sets in probeID that is in each selected gene set
整数向量表示探针设置在probeID这是在每个选定的基因组
参数:indexV
an integer vector containing positions for each 1s in the sparse indicator matrix
每1秒整数向量职位在稀疏指标矩阵
参数:indGused
an integer vector indicating which pathways in G were chosen
整数向量,表示在G途径选择
注意----------Note----------
See the help page for calculate.NTk or calculate.NEk
见calculate.NTk或calculate.NEk帮助页面
作者(S)----------Author(s)----------
Lu Tian, Peter Park, and Weil Lai
参考文献----------References----------
P.J. (2005) Discovering statistically significant pathways in expression profiling studies. Proceedings of the National Academy of Sciences of the USA, 102, 13544-9.
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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