predNuPoP(NuPoP)
predNuPoP()所属R语言包：NuPoP
R function for nucleosome positioning prediction, occupancy score and nucleosome binding affinity score calculation
核小体定位预测，占用得分和核小体的亲和力分数计算的R函数
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function invokes Fortran codes to compute the Viterbi prediction of nucleosome positioning, nucleosome occupancy score and nucleosome binding affinity score . A pre-trained linker DNA length distribution for the current species is used in a duration Hidden Markov model.
这个函数调用的Fortran代码来计算定位核小体，核小体占用的得分和核小体的亲和力评分维特比预测。一个训练有素的前连接器目前物种的DNA长度分布是用来在一个时间隐马尔可夫模型。
用法----------Usage----------
predNuPoP(file,species=7,model=4)
参数----------Arguments----------
参数：file
a string for the path and name of a DNA sequence file in FASTA format. This sequence file can be located in any directory. It must contain only one sequence of any length. By FASTA format, we require each line to be of the same length (the last line can be shorter; the first line should be '>sequenceName'). The length of each line should be not longer than 10 million bp.
为在FASTA格式的DNA序列文件的路径和名称的字符串。位于此序列文件可以在任何目录。它必须只包含一个任意长度的序列。 FASTA格式，我们需要每一行的长度相同（最后一行可以较短;第一行应该是> sequenceName）。每条线的长度应不超过10万基点。
参数：species
an integer from 0 to 11 as the label for a species indexed as follows: 1 = Human; 2 = Mouse; 3 = Rat; 4 = Zebrafish; 5 = D. melanogaster; 6 = C. elegans; 7 = S. cerevisiae; 8 = C. albicans; 9 = S. pombe; 10 = A. thaliana; 11 = Maize; 0 = Other. The default is 7 = S. cerevisiae . If species=0 is specified, NuPoP will identify a species from 1-11 that has most similar base composition to the input sequence, and then use the models from the selected species for prediction.
一个整数，从0到11索引作为一个物种的标签如下：1人; 2 =鼠标; 3 =鼠; 4 =斑马鱼5 =果蝇; 6 =线虫; 7 =酿酒酵母; 8 =白念珠菌; 9 =裂殖酵母; 10 =拟南芥; 11 =玉米; 0 =其他。默认是7 =酿酒酵母。如果species=0指定NuPoP将确定一个物种从1-11具有输入序列最相似的碱基组成，然后使用选定物种的预测模型。
参数：model
an integer = 4 or 1. NuPoP has two models integrated. One is the first order Markov chain for both nucleosome and linker DNA states. The other is 4th order (default). The latter distinguishes nucleosome/linker in up to 5-mer usage, and thus is slightly more effective in prediction, but runs slower. The time used by 4th order model is about 2.5 times of the 1st order model.
一个整数= 4或1。 NuPoP有两个模型集成。一个是一阶马尔可夫链核小体和DNA连接状态。另一种是4阶（默认）。后者区分核小体/连接器在5夏季使用，因而是稍微更有效的预测，但运行速度较慢。四阶模型所用的时间是一阶模型的约2.5倍。
值----------Value----------
predNuPoP outputs the prediction results into the current working directory. The output file is named after the input file with an added extension _Prediction1.txt or _Prediction4.txt, where 1 or 4 stands for the order of Markov chain models specified. The output file has five columns, Position, P-start, Occup, N/L, Affinity:
predNuPoP输出到当前工作目录的预测结果。输出文件后添加的扩展_Prediction1.txt或_Prediction4.txt，其中1或4马尔可夫链模型的顺序看台指定输入文件被命名为。输出文件有五列，Position，P-start，Occup，N/L，Affinity：
参数：Position
position in the input DNA sequence
输入DNA序列中的位置
参数：P-start
probability that the current position is the start of a nucleosome
概率当前的位置是一个核小体的开始
参数：Occup
nucleosome occupancy score
核小体占用评分
参数：N/L
nucleosome (1) or linker (0) for each position based on Viterbi prediction
核小体（1）或基于维特比预测的每一个位置的链接（0）
参数：Affinity
nucleosome binding affinity score
核小体结合亲和力得分
举例----------Examples----------
library(NuPoP)
predNuPoP(system.file("extdata", "test.seq", package="NuPoP"),species=7,model=4)
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 2012-2-26 07:58:19
