pairwiseAlignment(Biostrings)

pairwiseAlignment()所属R语言包：Biostrings

Optimal Pairwise Alignment

最佳成对排列

译者：生物统计家园网 机器人LoveR

描述----------Description----------

Solves (Needleman-Wunsch) global alignment, (Smith-Waterman) local alignment, and (ends-free) overlap alignment problems.

解决(Needleman文施)全球对齐，(Smith-Waterman算法)地方对齐，(完)重叠对齐问题。

用法----------Usage----------

pairwiseAlignment(pattern, subject, ...)

## S4 method for signature 'XStringSet,XStringSet'

pairwiseAlignment(pattern, subject,

patternQuality = PhredQuality(22L), subjectQuality = PhredQuality(22L),

type = "global", substitutionMatrix = NULL, fuzzyMatrix = NULL,

gapOpening = -10, gapExtension = -4, scoreOnly = FALSE)

## S4 method for signature 'QualityScaledXStringSet,QualityScaledXStringSet'

pairwiseAlignment(pattern, subject,

type = "global", substitutionMatrix = NULL, fuzzyMatrix = NULL,

gapOpening = -10, gapExtension = -4, scoreOnly = FALSE)

参数----------Arguments----------

参数：pattern

a character vector of any length, an XString, or an XStringSet object.

一个任意长度的字符向量，：XString或XStringSet对象。

参数：subject

a character vector of length 1 or an XString object.

一个字符长度为1的或XString对象的向量。

参数：patternQuality, subjectQuality

objects of class XStringQuality representing the respective quality scores for pattern and subject that are used in a quality-based method for generating a substitution matrix. These two arguments are ignored if !is.null(substitutionMatrix) or if its respective string set (pattern, subject) is of class QualityScaledXStringSet.

类对象XStringQualitypattern和subject是为质量为基础的方法，产生一个置换矩阵代表各自的质量分数。这两个参数被忽略如果!is.null(substitutionMatrix)或者其各自的字符串集(pattern，subject)类QualityScaledXStringSet。

参数：type

type of alignment. One of "global", "local", "overlap", "global-local", and "local-global" where "global" = align whole strings with end gap penalties, "local" = align string fragments, "overlap" = align whole strings without end gap penalties, "global-local" = align whole strings in pattern with consecutive subsequence of subject, "local-global" = align consecutive subsequence of pattern with whole strings in subject.

对齐类型。 "global"，"local"，"overlap"，"global-local"，"local-global"其中"global"=对齐结尾差距处罚的整个字符串，=对齐字符串碎片，"local"=调整没有结束的差距处罚的整个字符串，"overlap"=对齐整个字符串"global-local"pattern，subject连续序列=对齐连续序列"local-global"与pattern整个字符串。

参数：substitutionMatrix

substitution matrix representing the fixed substitution scores for an alignment. It cannot be used in conjunction with patternQuality and subjectQuality arguments.

替代矩阵对齐为代表的固定替代分数。不能patternQuality和subjectQuality参数一起使用。

参数：fuzzyMatrix

fuzzy match matrix for quality-based alignments. It takes values between 0 and 1; where 0 is an unambiguous mismatch, 1 is an unambiguous match, and values in between represent a fraction of "matchiness". (See details section below.)

模糊匹配矩阵为基础的质量路线。 0和1之间的值，其中0是一个明确的不匹配，是一个明确的比赛，和值之间的代表了“matchiness”的分数。 (见细节下文。)

参数：gapOpening

the cost for opening a gap in the alignment.

成本开放对齐的差距。

参数：gapExtension

the incremental cost incurred along the length of the gap in the alignment.

沿长度对齐的差距产生的增量成本。

参数：scoreOnly

logical to denote whether or not to return just the scores of the optimal pairwise alignment.

逻辑表示是否返回只是最佳配对对齐的分数。

参数：...

optional arguments to generic function to support additional methods.

可选参数的通用功能，以支持额外的方法。

Details

详情----------Details----------

Quality-based alignments are based on the paper the Bioinformatics article by Ketil Malde listed in the Reference section below. Let ε_i be the probability of an error in the base read. For "Phred" quality measures Q in [0, 99], these error probabilities are given by ε_i = 10^{-Q/10}. For "Solexa" quality measures Q in [-5, 99], they are given by ε_i = 1 - 1/(1 + 10^{-Q/10}). Assuming independence within and between base reads, the combined error probability of a mismatch when the underlying bases do match is ε_c = ε_1 + ε_2 - (n/(n-1)) * ε_1 * ε_2, where n is the number of letters in the underlying alphabet (i.e. n = 4 for DNA input, n = 20 for amino acid input, otherwise n is the number of distinct letters in the input). Using ε_c, the substitution score is given by b * \log_2(γ_{x,y} * (1 - ε_c) * n + (1 - γ_{x,y}) * ε_c * (n/(n-1))), where b is the bit-scaling for the scoring and γ_{x,y} is the probability that characters x and y represents the same underlying information (e.g. using IUPAC, γ_{A,A} = 1 and γ_{A,N} = 1/4. In the arguments listed above fuzzyMatch represents γ_{x,y} and patternQuality and subjectQuality represents ε_1 and ε_2 respectively.

基于质量的路线是基于Ketil Malde纸下面的“参考”部分中列出的生物信息学的文章。让ε_i是一个错误的阅读碱基的可能性。为"Phred"质量的措施Q[0, 99]，这些错误的概率ε_i = 10^{-Q/10}。为"Solexa"质量的措施Q[-5, 99]，ε_i = 1 - 1/(1 + 10^{-Q/10})。假设内与碱基读取的独立性，不匹配的组合错误的可能性时，底层的基础不匹配是ε_c = ε_1 + ε_2 - (n/(n-1)) * ε_1 * ε_2，其中n的基本字母表中的字母(即n = 4 DNA输入，n = 20为氨基酸投入，否则n是在输入不同的字母)。使用ε_c，替代得分b * \log_2(γ_{x,y} * (1 - ε_c) * n + (1 - γ_{x,y}) * ε_c * (n/(n-1)))，b是位缩放得分γ_{x,y}的概率是字符x“ y代表相同的基本信息(例如，使用国际化联，γ_{A,A} = 1和γ_{A,N} = 1/4以上fuzzyMatch列出的论点。γ_{x,y}和patternQuality“的subjectQuality指ε_1和ε_2分别。

If scoreOnly == FALSE, a pairwise alignment with the maximum alignment score is returned. If more than one pairwise alignment produces the maximum alignment score, then the alignment with the smallest initial deletion whose mismatches occur before its insertions and deletions is chosen. For example, if pattern = "AGTA" and subject = "AACTAACTA", then the alignment pattern: [1] AG-TA; subject: [1] AACTA is chosen over pattern: [1] A-GTA; subject: [1] AACTA or pattern: [1] AG-TA; subject: [5] AACTA if they all achieve the maximum alignment score.

如果scoreOnly == FALSE，返回与最大比对得分的成对对齐。如果多个成对对齐的生产对齐得分最高，然后用最小的初始删除的不匹配发生之前，插入和删除选择的路线。例如，如果pattern = "AGTA"和subject = "AACTAACTA"，然后对齐pattern: [1] AG-TA; subject: [1] AACTA选择了pattern: [1] A-GTA; subject: [1] AACTA或pattern: [1] AG-TA; subject: [5] AACTA如果他们都达到最大对齐得分。

值----------Value----------

If scoreOnly == FALSE, an instance of class PairwiseAlignedXStringSet or PairwiseAlignedFixedSubject is returned. If scoreOnly == TRUE, a numeric vector containing the scores for the optimal pairwise alignments is returned.

如果scoreOnly == FALSE，一个类的实例PairwiseAlignedXStringSet或PairwiseAlignedFixedSubject退回。如果scoreOnly == TRUE，数字向量的分数为最佳配对路线返回。

注意----------Note----------

Use matchPattern or vmatchPattern if you need to find all the occurrences (eventually with indels) of a given pattern in a reference sequence or set of sequences.

使用matchPattern或vmatchPattern如果你需要找到所有出现在给定的模式参考序列或一组序列(最终INDELS)。

Use matchPDict if you need to match a (big) set of patterns against a reference sequence.

使用matchPDict如果你需要匹配的模式对参考序列(大)集。

作者(S)----------Author(s)----------

P. Aboyoun and H. Pages

参考文献----------References----------

参见----------See Also----------

stringDist, PairwiseAlignedXStringSet-class, XStringQuality-class, substitution.matrices, matchPattern

stringDist，PairwiseAlignedXStringSet级，XStringQuality级，substitution.matrices，matchPattern

举例----------Examples----------

## Nucleotide global, local, and overlap alignments[＃核苷酸全球，地方和重叠路线]

s1

DNAString("ACTTCACCAGCTCCCTGGCGGTAAGTTGATCAAAGGAAACGCAAAGTTTTCAAG")

s2

DNAString("GTTTCACTACTTCCTTTCGGGTAAGTAAATATATAAATATATAAAAATATAATTTTCATC")

# First use a fixed substitution matrix[首先使用一个固定的替代矩阵]

mat

globalAlign

pairwiseAlignment(s1, s2, substitutionMatrix = mat,

gapOpening = -5, gapExtension = -2)

localAlign

pairwiseAlignment(s1, s2, type = "local", substitutionMatrix = mat,

gapOpening = -5, gapExtension = -2)

overlapAlign

pairwiseAlignment(s1, s2, type = "overlap", substitutionMatrix = mat,

gapOpening = -5, gapExtension = -2)

# Then use quality-based method for generating a substitution matrix[然后使用基于质量的方法，产生一个置换矩阵]

pairwiseAlignment(s1, s2,

patternQuality = SolexaQuality(rep(c(22L, 12L), times = c(36, 18))),

subjectQuality = SolexaQuality(rep(c(22L, 12L), times = c(40, 20))),

scoreOnly = TRUE)

# Now assume can't distinguish between C/T and G/A[现在，假设不能区分的C / T和G / A]

pairwiseAlignment(s1, s2,

patternQuality = SolexaQuality(rep(c(22L, 12L), times = c(36, 18))),

subjectQuality = SolexaQuality(rep(c(22L, 12L), times = c(40, 20))),

type = "local")

mapping

dimnames(mapping)

mapping["C", "T"]

mapping["G", "A"]

pairwiseAlignment(s1, s2,

patternQuality = SolexaQuality(rep(c(22L, 12L), times = c(36, 18))),

subjectQuality = SolexaQuality(rep(c(22L, 12L), times = c(40, 20))),

fuzzyMatrix = mapping,

type = "local")

## Amino acid global alignment[＃氨基酸全球对齐]

pairwiseAlignment(AAString("PAWHEAE"), AAString("HEAGAWGHEE"),

substitutionMatrix = "BLOSUM50",

gapOpening = 0, gapExtension = -8)

转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。

注：

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