cai(seqinr)
cai()所属R语言包：seqinr
Codon Adaptation Index
密码子适应指数
译者：生物统计家园网 机器人LoveR
描述----------Description----------
The Codon Adaptation Index (Sharp and Li 1987) is the most popular index of gene expressivity with about 1000 citations 20 years after its publication. Its values range from 0 (low) to 1 (high). The implementation here is intended to work exactly as in the program codonW written by by John Peden during his PhD thesis under the supervision of P.M. Sharp.
密码子适应指数（夏普和Li，1987）是最流行的指数的基因表现力与约1000出版20年后的引用。其值的范围是从0（低）到1（高）。这里的实现，正是由于在工作程序“codonW写的PM的监督下，由约翰·佩登在他的博士论文夏普。
用法----------Usage----------
cai(seq, w, numcode = 1, zero.threshold = 0.0001, zero.to = 0.01)
参数----------Arguments----------
参数：seq
a coding sequence as a vector of single characters
作为向量的单个字符的编码序列
参数：w
a vector for the relative adaptiveness of each codon
每个密码子的相对的适应能力的向量
参数：numcode
the genetic code number as in translate
遗传密码如translate
参数：zero.threshold
a value in w below this threshold is considered as zero
w低于这个阈值的值被认为是零
参数：zero.to
a value considered as zero in w is forced to this value. The default is from Bulmer (1988).
视为零的值，在w被强制到这个值。默认情况下是从布尔默（1988年）。
Details
详细信息----------Details----------
Adapted from the documentation of the CAI function in the program codonW writen by John Peden: CAI is a measurement of the relative adaptiveness of the codon usage of a gene towards the codon usage of highly expressed genes. The relative adaptiveness (w) of each codon is the ratio of the usage of each codon, to that of the most abundant codon for the same amino acid. The CAI index is defined as the geometric mean of these relative adaptiveness values. Non-synonymous codons and termination codons (genetic code dependent) are excluded. To aid computation, the CAI is calculated as using a natural log summation, To prevent a codon having a relative adaptiveness value of zero, which could result in a CAI of zero; these codons have fitness of zero (<.0001) are adjusted to 0.01.
改编自codonW书面上由约翰·佩登：CAI是一个相对的适应能力，对高表达基因的密码子使用的基因的密码子使用的测量程序“的CAI功能的文档。 （w）的每个密码子的相对的适应能力是每个密码子的使用量的比率，最丰富的相同的氨基酸的密码子。这些相对的适应能力值的几何平均值的CAI指数被定义为。不包括非同义密码子和终止密码子（遗传密码而定）。为了帮助计算，CAI使用自然对数求和计算，为了防止具有相对的适应能力的零值，这可能导致在零的CAI的密码子，这些密码子有健身为零（P <.0001）的调整为0.01。
值----------Value----------
A single numerical value for the CAI.
一个单一的数值的CAI。
（作者）----------Author(s)----------
J.R. Lobry
参考文献----------References----------
measure of directional synonymous codon usage bias, and its potential applications. Nucleic Acids Research, 15:1281-1295.
Are codon usage patterns in unicellular organisms determined by selection-mutation balance. Journal of Evolutionary Biology, 1:15-26.
Analysis of codon usage. PhD Thesis, University of Nottingham, UK.
http://codonw.sourceforge.net/ under a GPL licence.
参见----------See Also----------
caitab for some w values from codonW. uco for codon usage tabulation.
caitab一些w值codonW的。 uco密码子使用的表格。
实例----------Examples----------
#[]
# How to reproduce the results obtained with the C program codonW[如何重现的C程序codonW获得的结果]
# version 1.4.4 writen by John Peden. We use here the "input.dat"[由约翰·佩登版本1.4.4书面上。我们在这里使用“INPUT.DAT”]
# test file from codonW (Saccharomyces cerevisiae).[来自codonW（酿酒酵母（Saccharomyces cerevisiae））的测试文件。]
#[]
inputdatfile <- system.file("sequences/input.dat", package = "seqinr")
input <- read.fasta(file = inputdatfile) # read the FASTA file[阅读FASTA文件]
#[]
# Import results obtained with codonW[进口得到的结果与codonW]
#[]
scucofile <- system.file("sequences/scuco.txt", package = "seqinr")
scuco.res <- read.table(scucofile, header = TRUE) # read codonW result file[读codonW结果文件]
#[]
# Use w for Saccharomyces cerevisiae[使用w酿酒酵母（Saccharomyces cerevisiae）]
#[]
data(caitab)
w <- caitab$sc
#[]
# Compute CAI and compare results:[计算CAI和比较结果：]
#[]
cai.res <- sapply(input, cai, w = w)
plot(cai.res, scuco.res$CAI,
main = "Comparison of seqinR and codonW results",
xlab = "CAI from seqinR",
ylab = "CAI from codonW",
las = 1)
abline(c(0,1))
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 2012-9-30 01:14:37
