startScore(ChIPseqR)
startScore()所属R语言包:ChIPseqR
Score potential protein binding sites
分数潜在蛋白结合位点
译者:生物统计家园网 机器人LoveR
描述----------Description----------
For each position in the genome this function computes a score indicating the likelihood that a protein binding site starts at that position.
对于每个基因组中的位置,此功能指示的蛋白质结合位点的可能性,在那个位置开始计算得分。
用法----------Usage----------
startScore(data, b, support, background, bgCutoff, supCutoff)
参数----------Arguments----------
参数:data
A two column matrix with read counts. The two columns correspond to reads on the forward and reverse strand respectively.
一个两列矩阵读取计数。两列对应分别正向和反向链读取。
参数:b
Length of binding region.
结合区域的长度。
参数:support
Length of support region.
支持区域的长度。
参数:background
Length of background window.
背景窗口的长度。
参数:bgCutoff
Cutoff for the change in read rates between adjacent windows (see Details).
截止在相邻窗口的读取率的变化(见详情)。
参数:supCutoff
Cutoff for the change in read rates between support regions on forward and reverse strand (see Details).
截止正向和反向链支持的区域之间的读取率的变化(见详情)。
Details
详情----------Details----------
Robust estimates of read rates in background windows and support regions are obtained by limiting the difference between related estimates. Consider a forward support region of length 10 containing 20 reads. The maximum likelihood estimate for the rate parameter of the (assumed) underlying Poisson distribution is lambda_hat = 20/10 = 2. If there are 50 reads in the reverse support region a robust estimate of the rate parameter is obtained as max(50/10, qpois(supCutoff, lambda=lambda_hat))
鲁棒估计在背景窗口和支持区域的读取率获得通过限制有关估计数之间的差异。考虑长度10载20人读取提出的支持区域。率(假设)基本泊松分布参数的最大似然估计是lambda_hat = 20/10 = 2。如果有50个读取率参数的稳健估计为max(50/10, qpois(supCutoff, lambda=lambda_hat))获得反向支撑区域
值----------Value----------
Numeric vector with binding site scores.
数字向量的结合位点的分数。
注意----------Note----------
Instead of calling this function directly use callBindingSites.
,而不是直接调用此函数使用callBindingSites。
作者(S)----------Author(s)----------
Peter Humburg
参见----------See Also----------
callBindingSites
callBindingSites
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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