| Title: | Multiple Sequence Alignment |
|---|---|
| Description: | The 'msa' package provides a unified R/Bioconductor interface to the multiple sequence alignment algorithms ClustalW, ClustalOmega, and Muscle. All three algorithms are integrated in the package, therefore, they do not depend on any external software tools and are available for all major platforms. The multiple sequence alignment algorithms are complemented by a function for pretty-printing multiple sequence alignments using the LaTeX package TeXshade. |
| Authors: | Enrico Bonatesta [aut], Christoph Kainrath [aut], Ulrich Bodenhofer [aut,cre] |
| Maintainer: | Ulrich Bodenhofer <[email protected]> |
| License: | GPL (>= 2) |
| Version: | 1.39.0 |
| Built: | 2024-11-03 06:25:57 UTC |
| Source: | https://github.com/bioc/msa |
The msa package provides a unified R/Bioconductor interface to different multiple sequence alignment algorithms. Currently, ‘ClustalW’, ‘ClustalOmega’, and ‘MUSCLE’ are supported. All algorithms are usable without additional software packages and on all major platforms. The multiple sequence algorithms are complemented by an R interface to the powerful LaTeX package texshade.sty which allows for a highly customizable plots of multiple sequence alignments.
The central method of this package is msa.
It provides unified access to all three multiple alignment algorithms
implemented in this package. The function (like the three functions
directly accessing the respective algorithm, i.e.,
msaClustalW, msaClustalOmega, and
msaMuscle) can handle multiple types of input sequences,
such as XStringSet and any subclass thereof,
character vectors, and can also directly read from FASTA files.
The package defines special classes for storing multiple alignments
and provides several methods for manipulating, analyzing, and printing
such multiple alignments. The function msaPrettyPrint
provides an interface to the powerful TeXshade package that allows for
powerful LaTeX-based visualization of multiple alignments.
Enrico Bonatesta, Christoph Kainrath, and Ulrich Bodenhofer
Bodenhofer, U., Bonatesta, E., Horejs-Kainrath, C., and Hochreiter, S. (2015). msa: an R package for multiple sequence alignment. Bioinformatics 31(24):3997-3999. DOI: doi:10.1093/bioinformatics/btv494.
Thompson, J. D., Higgins, D. G., and Gibson, T. J. (1994). CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res. 22(22):4673-4680. DOI: doi:10.1093/nar/22.22.4673.
Sievers, F., Wilm, A., Dineen, D., Gibson, T. J., Karplus, K., Li, W., Lopez, R., McWilliam, H., Remmert, M., Soeding, J., Thompson, J. D., and Higgins, D. G. (2011). Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega. Mol. Syst. Biol. 7:539. DOI: doi:10.1038/msb.2011.75.
Edgar, R. C. (2004). MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 32(5):1792-1797. DOI: doi:10.1093/nar/gkh340.
Edgar, R. C. (2004). MUSCLE: a multiple sequence alignment method with reduced time and space complexity. BMC Bioinformatics 5:113. DOI: doi:10.1186/1471-2105-5-113.
Beitz, E. (2000). TeXshade: shading and labeling of multiple sequence alignments using LaTeX2e. Bioinformatics 16(2):135-139. DOI: doi:10.1093/bioinformatics/16.2.135.
msa, msaClustalW,
msaClustalOmega, msaMuscle,
msaPrettyPrint
## read sequences filepath <- system.file("examples", "exampleAA.fasta", package="msa") mySeqs <- readAAStringSet(filepath) ## call unified interface msa() for default method (ClustalW) and ## default parameters msa(mySeqs)## read sequences filepath <- system.file("examples", "exampleAA.fasta", package="msa") mySeqs <- readAAStringSet(filepath) ## call unified interface msa() for default method (ClustalW) and ## default parameters msa(mySeqs)
The msa function provides a unified interface to
the three multiple sequence alignment algorithms in this package:
‘ClustalW’, ‘ClustalOmega’, and ‘MUSCLE’.
msa(inputSeqs, method=c("ClustalW", "ClustalOmega", "Muscle"), cluster="default", gapOpening="default", gapExtension="default", maxiters="default", substitutionMatrix="default", type="default", order=c("aligned", "input"), verbose=FALSE, help=FALSE, ...)msa(inputSeqs, method=c("ClustalW", "ClustalOmega", "Muscle"), cluster="default", gapOpening="default", gapExtension="default", maxiters="default", substitutionMatrix="default", type="default", order=c("aligned", "input"), verbose=FALSE, help=FALSE, ...)
inputSeqs |
input sequences; this argument can be a character vector,
an object of class |
method |
specifies the multiple sequence alignment to be used;
currently, |
cluster |
parameter related to sequence clustering; its
interpretation and default value depends on the method;
see |
gapOpening |
gap opening penalty; the defaults are
specific to the algorithm (see |
gapExtension |
gap extension penalty; the defaults are
specific to the algorithm (see |
maxiters |
maximum number of iterations; its
interpretation and default value depends on the method;
see |
substitutionMatrix |
substitution matrix for scoring matches and
mismatches; format and defaults depend on the algorithm;
see |
type |
type of the input sequences |
order |
how the sequences should be ordered in the output object;
if |
verbose |
if |
help |
if |
... |
all other parameters are passed on to the multiple
sequence algorithm, i.e. to one of the functions
|
msa is a simple wrapper function that unifies the interfaces of
the three functions msaClustalW,
msaClustalOmega, and msaMuscle. Which
function is called, is controlled by the method argument.
Note that the input sequences may be reordered by the multiple
sequence alignment algorithms in order to group together similar
sequences (see also description of argument order above).
So, if the input order should be preserved or if the input order
should be recovered later, we strongly recommend to always assign
unique names to the input sequences. As noted in the description
of the inputSeqs argument above, all functions, msa(),
msaClustalW, msaClustalOmega, and
msaMuscle, also allow
for direct reading from FASTA files. This is mainly for the reason of
memory efficiency if the sequence data set is very large. Otherwise,
we want to encourage users to first read the sequences into the R
workspace. If sequences are read from a FASTA file
directly, the order of output sequences is completely under
the control of the respective
algorithm and does not allow for checking whether the sequences are
named uniquely in the FASTA file. The preservation of the input order
works also for sequence data read from a FASTA file, but only for
ClustalW and ClustalOmega; MUSCLE does not support this (see also
argument order above and msaMuscle).
Depending on the type of sequences for which it was called,
msa returns a MsaAAMultipleAlignment,
MsaDNAMultipleAlignment, or
MsaRNAMultipleAlignment object.
If called with help=TRUE, msa returns
an invisible NULL.
Enrico Bonatesta and Christoph Kainrath
Bodenhofer, U., Bonatesta, E., Horejs-Kainrath, C., and Hochreiter, S. (2015). msa: an R package for multiple sequence alignment. Bioinformatics 31(24):3997-3999. DOI: doi:10.1093/bioinformatics/btv494.
http://www.clustal.org/download/clustalw_help.txt
http://www.clustal.org/omega/README
http://www.drive5.com/muscle/muscle.html
Thompson, J. D., Higgins, D. G., and Gibson, T. J. (1994) CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res. 22(22):4673-4680. DOI: doi:10.1093/nar/22.22.4673.
Sievers, F., Wilm, A., Dineen, D., Gibson, T. J., Karplus, K., Li, W., Lopez, R., McWilliam, H., Remmert, M., Soeding, J., Thompson, J. D., and Higgins, D. G. (2011) Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega. Mol. Syst. Biol. 7:539. DOI: doi:10.1038/msb.2011.75.
Edgar, R. C. (2004) MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 32(5):1792-1797. DOI: doi:10.1093/nar/gkh340.
Edgar, R. C. (2004) MUSCLE: a multiple sequence alignment method with reduced time and space complexity. BMC Bioinformatics 5:113. DOI: doi:10.1186/1471-2105-5-113.
msaClustalW,
msaClustalOmega, msaMuscle,
msaPrettyPrint, MsaAAMultipleAlignment,
MsaDNAMultipleAlignment,
MsaRNAMultipleAlignment,
MsaMetaData
## read sequences filepath <- system.file("examples", "exampleAA.fasta", package="msa") mySeqs <- readAAStringSet(filepath) ## call unified interface msa() for default method (ClustalW) and ## default parameters msa(mySeqs) ## call ClustalOmega through unified interface msa(mySeqs, method="ClustalOmega") ## call MUSCLE through unified interface with some custom parameters msa(mySeqs, method="Muscle", gapOpening=12, gapExtension=3, maxiters=16, cluster="upgmamax", SUEFF=0.4, brenner=FALSE, order="input", verbose=FALSE)## read sequences filepath <- system.file("examples", "exampleAA.fasta", package="msa") mySeqs <- readAAStringSet(filepath) ## call unified interface msa() for default method (ClustalW) and ## default parameters msa(mySeqs) ## call ClustalOmega through unified interface msa(mySeqs, method="ClustalOmega") ## call MUSCLE through unified interface with some custom parameters msa(mySeqs, method="Muscle", gapOpening=12, gapExtension=3, maxiters=16, cluster="upgmamax", SUEFF=0.4, brenner=FALSE, order="input", verbose=FALSE)
This function checks and fixed sequence names of multiple
alignment objects if they contain characters
that might lead to LaTeX problems when using
msaPrettyPrint.
msaCheckNames(x, replacement=" ", verbose=TRUE)msaCheckNames(x, replacement=" ", verbose=TRUE)
x |
an object of class |
replacement |
a character string specifying with which character(s) potentially problematic characters should be replaced. |
verbose |
if |
The Biostrings package does not impose any restrictions on
the names of sequences. Consequently, msa also allows all
possible ASCII strings as sequence (row) names in multiple alignments.
As soon as msaPrettyPrint is used for pretty-printing
multiple sequence alignments, however, the sequence names are
interpreted as plain LaTeX source code. Consequently, LaTeX errors
may arise because of characters or words in the sequence names that LaTeX
does not or cannot interpret as plain text correctly. This
particularly includes appearances of special characters and backslash
characters in the sequence names.
The msaCheckNames function takes a multiple alignment object
and checks sequence names for possibly problematic characters, which
are all characters but letters (upper and lower case), digits,
spaces, commas, colons, semicolons, periods, question and exclamation
marks, dashes, braces, single quotes, and double quotes.
All other characters are
considered problematic. The function allows for both checking and
fixing the sequence names. If called with verbose=TRUE
(default), the function prints a warning if a problematic character is
found. At the same time, regardless of the verbose argument,
the function invisibly returns a copy of x in whose sequence
names all problematic characters have been replaced by the string
that is supplied via the replacement argument (the default is
a single space).
In any case, the best solution is to check sequence names carefully and to avoid problematic sequence names from the beginning.
The function invisibly returns a copy of the argument x
(therefore, an object of the same class as x), but
with modified sequence/row names (see details above).
Ulrich Bodenhofer
Bodenhofer, U., Bonatesta, E., Horejs-Kainrath, C., and Hochreiter, S. (2015). msa: an R package for multiple sequence alignment. Bioinformatics 31(24):3997-3999. DOI: doi:10.1093/bioinformatics/btv494.
msaPrettyPrint,
MsaAAMultipleAlignment,
MsaDNAMultipleAlignment,
MsaRNAMultipleAlignment
## create toy example mySeqs <- DNAStringSet(c("ACGATCGATC", "ACGACGATC", "ACGATCCCCC")) names(mySeqs) <- c("Seq. #1", "Seq. \2", "Seq. ~3") ## perform multiple alignment myAlignment <- msa(mySeqs) myAlignment ## check names msaCheckNames(myAlignment) ## fix names myAlignment <- msaCheckNames(myAlignment, replacement="", verbose=FALSE) myAlignment## create toy example mySeqs <- DNAStringSet(c("ACGATCGATC", "ACGACGATC", "ACGATCCCCC")) names(mySeqs) <- c("Seq. #1", "Seq. \2", "Seq. ~3") ## perform multiple alignment myAlignment <- msa(mySeqs) myAlignment ## check names msaCheckNames(myAlignment) ## fix names myAlignment <- msaCheckNames(myAlignment, replacement="", verbose=FALSE) myAlignment
This function calls the multiple sequence alignment algorithm ClustalOmega.
msaClustalOmega(inputSeqs, cluster="default", gapOpening="default", gapExtension="default", maxiters="default", substitutionMatrix="default", type="default", order=c("aligned", "input"), verbose=FALSE, help=FALSE, ...)msaClustalOmega(inputSeqs, cluster="default", gapOpening="default", gapExtension="default", maxiters="default", substitutionMatrix="default", type="default", order=c("aligned", "input"), verbose=FALSE, help=FALSE, ...)
inputSeqs |
input sequences; see |
cluster |
The cluster size which should be used. The default is 100.
In the original ClustalOmega implementation, this parameter is called
|
gapOpening, gapExtension
|
ClustalOmega currently does
not allow to adjust gap penalties; these arguments are only for
future extensions and consistency with the other algorithms
and |
maxiters |
maximum number of iterations; the default value is 0
(no limitation). In the original ClustalOmega implementation, this
parameter is called |
substitutionMatrix |
name of substitution matrix for scoring matches and
mismatches; can be one of the choices
|
type |
type of the input sequences |
order |
how the sequences should be ordered in the output object
(see |
verbose |
if |
help |
if |
... |
further parameters specific to ClustalOmega;
An overview of parameters that are available in this interface
is shown when calling |
This is a function providing the ClustalOmega multiple alignment
algorithm as an R function. It can be used for various types of
sequence data (see inputSeqs argument above). Parameters that
are common to all multiple sequences alignments provided by the
msa package are explicitly provided by the function and named
in the same for all algorithms. Most other parameters that are
specific to ClustalOmega can be passed to ClustalOmega via additional
arguments (see argument help above).
Since ClustalOmega only allows for using built-in amino acid substitution matrices, it is hardly useful for multiple alignments of nucleotide sequences.
For a note on the order of output sequences and direct reading from
FASTA files, see msa.
Depending on the type of sequences for which it was called,
msaClustalOmega returns a
MsaAAMultipleAlignment,
MsaDNAMultipleAlignment, or
MsaRNAMultipleAlignment object.
If called with help=TRUE, msaClustalOmega returns
an invisible NULL.
Enrico Bonatesta and Christoph Kainrath
Bodenhofer, U., Bonatesta, E., Horejs-Kainrath, C., and Hochreiter, S. (2015). msa: an R package for multiple sequence alignment. Bioinformatics 31(24):3997-3999. DOI: doi:10.1093/bioinformatics/btv494.
http://www.clustal.org/omega/README
Sievers, F., Wilm, A., Dineen, D., Gibson, T. J., Karplus, K., Li, W., Lopez, R., McWilliam, H., Remmert, M., Soeding, J., Thompson, J. D., and Higgins, D. G. (2011) Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega. Mol. Syst. Biol. 7:539. DOI: doi:10.1038/msb.2011.75.
msa, MsaAAMultipleAlignment,
MsaDNAMultipleAlignment,
MsaRNAMultipleAlignment,
MsaMetaData
## read sequences filepath <- system.file("examples", "exampleAA.fasta", package="msa") mySeqs <- readAAStringSet(filepath) ## call msaClustalOmega with default values msaClustalOmega(mySeqs) ## call msaClustalOmega with custom parameters msaClustalOmega(mySeqs, auto=FALSE, cluster=120, dealign=FALSE, useKimura=FALSE, order="input", verbose=FALSE)## read sequences filepath <- system.file("examples", "exampleAA.fasta", package="msa") mySeqs <- readAAStringSet(filepath) ## call msaClustalOmega with default values msaClustalOmega(mySeqs) ## call msaClustalOmega with custom parameters msaClustalOmega(mySeqs, auto=FALSE, cluster=120, dealign=FALSE, useKimura=FALSE, order="input", verbose=FALSE)
This function calls the multiple sequence alignment algorithm ClustalW.
msaClustalW(inputSeqs, cluster="default", gapOpening="default", gapExtension="default", maxiters="default", substitutionMatrix="default", type="default", order=c("aligned", "input"), verbose=FALSE, help=FALSE, ...)msaClustalW(inputSeqs, cluster="default", gapOpening="default", gapExtension="default", maxiters="default", substitutionMatrix="default", type="default", order=c("aligned", "input"), verbose=FALSE, help=FALSE, ...)
inputSeqs |
input sequences; see |
cluster |
The clustering method which should be used.
Possible values are |
gapOpening |
gap opening penalty; the default value for nucleotide sequences is 15.0, the default value for amino acid sequences is 10.0. |
gapExtension |
gap extension penalty; the default value for nucleotide sequences is 6.66, the default value for amino acid sequences is 0.2. |
maxiters |
maximum number of iterations; the default value is 16.
In the original ClustalW implementation, this parameter is called
|
substitutionMatrix |
substitution matrix for scoring matches and
mismatches; can be a real matrix, a file name, or the name of a
built-in substitution matrix. In the latter case, the choices
|
type |
type of the input sequences |
order |
how the sequences should be ordered in the output object
(see |
verbose |
if |
help |
if |
... |
further parameters specific to ClustalW;
An overview of parameters that are available in this interface
is shown when calling |
This is a function providing the ClustalW multiple alignment
algorithm as an R function. It can be used for various types of
sequence data (see inputSeqs argument above). Parameters that
are common to all multiple sequences alignments provided by the
msa package are explicitly provided by the function and named
in the same for all algorithms. Most other parameters that are
specific to ClustalW can be passed to ClustalW via additional
arguments (see argument help above).
For a note on the order of output sequences and direct reading from
FASTA files, see msa.
Depending on the type of sequences for which it was called,
msaClustalW returns a MsaAAMultipleAlignment,
MsaDNAMultipleAlignment, or
MsaRNAMultipleAlignment object.
If called with help=TRUE, msaClustalW returns
an invisible NULL.
Enrico Bonatesta and Christoph Kainrath
Bodenhofer, U., Bonatesta, E., Horejs-Kainrath, C., and Hochreiter, S. (2015). msa: an R package for multiple sequence alignment. Bioinformatics 31(24):3997-3999. DOI: doi:10.1093/bioinformatics/btv494.
http://www.clustal.org/download/clustalw_help.txt
Thompson, J. D., Higgins, D. G., and Gibson, T. J. (1994) CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res. 22(22):4673-4680. DOI: doi:10.1093/nar/22.22.4673.
msa, MsaAAMultipleAlignment,
MsaDNAMultipleAlignment,
MsaRNAMultipleAlignment,
MsaMetaData
## read sequences filepath <- system.file("examples", "exampleAA.fasta", package="msa") mySeqs <- readAAStringSet(filepath) ## call msaClustalW with default values msaClustalW(mySeqs) ## call msaClustalW with custom parameters msaClustalW(mySeqs, gapOpening=1, gapExtension=1, maxiters=16, kimura=FALSE, order="input", maxdiv=23)## read sequences filepath <- system.file("examples", "exampleAA.fasta", package="msa") mySeqs <- readAAStringSet(filepath) ## call msaClustalW with default values msaClustalW(mySeqs) ## call msaClustalW with custom parameters msaClustalW(mySeqs, gapOpening=1, gapExtension=1, maxiters=16, kimura=FALSE, order="input", maxdiv=23)
This method computes a consensus sequence from a multiple alignment or a previously computed consensus matrix. Currently, two different ways of these computations are available.
## S4 method for signature 'matrix' msaConsensusSequence(x, type=c("Biostrings", "upperlower"), thresh=c(80, 20), ignoreGaps=FALSE, ...) ## S4 method for signature 'MultipleAlignment' msaConsensusSequence(x, ...)## S4 method for signature 'matrix' msaConsensusSequence(x, type=c("Biostrings", "upperlower"), thresh=c(80, 20), ignoreGaps=FALSE, ...) ## S4 method for signature 'MultipleAlignment' msaConsensusSequence(x, ...)
x |
an object of class |
type |
a character string specifying how to compute the consensus
sequence. Currently, types |
thresh |
a decreasing two-element numeric vector of numbers
between 0 and 100 corresponding to the two conservation thresholds.
Only relevant for |
ignoreGaps |
a logical (default: |
... |
when the method is called for a
|
The method takes a MultipleAlignment object or a
previously computed consensus matrix and computes a consensus
sequence. For type="Biostrings", the method
consensusString from the Biostrings package is
used to compute the consensus sequence. For type="upperlower",
two thresholds (argument thresh, see above) are used to
compute the consensus sequence:
If the relative frequency of the most frequent letter at a given position is at least as large as the first threshold (default: 80%), then this most frequent letter is used for the consensus sequence at this position as it is.
If the relative frequency of the most frequent letter at a given position is smaller than the first threshold, but at least as large as the second threshold (default: 20%), then this most frequent letter is used for the consensus sequence at this position, but converted to lower case.
If the relative frequency of the most frequent letter in a column is even smaller than the second threshold, then a dot is used for the consensus sequence at this position.
If ignoreGaps=FALSE (which is the default),
gaps are treated like all other
letters except for the fact that obviously no lowercase conversion
takes place in case that the relative frequency is between the
two thresholds. If ignoreGaps=TRUE, gaps are ignored
completely, and the consensus sequence is computed from the
non-gap letters only.
If the consensus matrix of a multiple alignment of nucleotide sequences contains rows labeled ‘+’ and/or ‘.’, these rows are ignored.
The function returns a character string with the consensus sequence.
Ulrich Bodenhofer
Bodenhofer, U., Bonatesta, E., Horejs-Kainrath, C., and Hochreiter, S. (2015). msa: an R package for multiple sequence alignment. Bioinformatics 31(24):3997-3999. DOI: doi:10.1093/bioinformatics/btv494.
msa, MsaAAMultipleAlignment,
MsaDNAMultipleAlignment,
MsaRNAMultipleAlignment,
MsaMetaData,
MultipleAlignment,
consensusString
## read sequences filepath <- system.file("examples", "HemoglobinAA.fasta", package="msa") mySeqs <- readAAStringSet(filepath) ## perform multiple alignment myAlignment <- msa(mySeqs) ## regular consensus sequence using consensusString() method from the ## 'Biostrings' package msaConsensusSequence(myAlignment) ## use the other method msaConsensusSequence(myAlignment, type="upperlower") ## use the other method with custom parameters msaConsensusSequence(myAlignment, type="upperlower", thresh=c(50, 20), ignoreGaps=TRUE) ## compute a consensus matrix first conMat <- consensusMatrix(myAlignment) msaConsensusSequence(conMat)## read sequences filepath <- system.file("examples", "HemoglobinAA.fasta", package="msa") mySeqs <- readAAStringSet(filepath) ## perform multiple alignment myAlignment <- msa(mySeqs) ## regular consensus sequence using consensusString() method from the ## 'Biostrings' package msaConsensusSequence(myAlignment) ## use the other method msaConsensusSequence(myAlignment, type="upperlower") ## use the other method with custom parameters msaConsensusSequence(myAlignment, type="upperlower", thresh=c(50, 20), ignoreGaps=TRUE) ## compute a consensus matrix first conMat <- consensusMatrix(myAlignment) msaConsensusSequence(conMat)
This method computes a vector of conservation scores from a multiple alignment or a previously computed consensus matrix.
## S4 method for signature 'matrix' msaConservationScore(x, substitutionMatrix, gapVsGap=NULL, ...) ## S4 method for signature 'MultipleAlignment' msaConservationScore(x, ...)## S4 method for signature 'matrix' msaConservationScore(x, substitutionMatrix, gapVsGap=NULL, ...) ## S4 method for signature 'MultipleAlignment' msaConservationScore(x, ...)
x |
an object of class |
substitutionMatrix |
substitution matrix (see details below). |
gapVsGap |
score to use for aligning gaps versus gaps (see details below). |
... |
when the method is called for a
|
The method takes a MultipleAlignment object or a
previously computed consensus matrix and computes the sum of pairwise
scores for all positions of the alignment. For computing these scores,
it is compulsory to specify a substitution/scoring matrix. This matrix
must be provided as a matrix object. This can either be
one of the ready-made matrices provided by the pwalign
package (e.g. BLOSUM62) or any other hand-crafted
matrix. In the latter case, the following restrictions apply:
The matrix must be quadratic.
For reasonable results, the matrix should be symmetric (note that this is not checked).
Rows and columns must be named and the order of letters/symbols in row names and column names must be identical.
All letters/symbols occurring in the multiple alignment, including gaps ‘-’, must also be found in the row/column names of the substitution matrix. For consistency with the matrices from the pwalign package, the row/column corresponding to gap penalties may also be labeled ‘*’ instead of ‘-’.
So, nucleotide substitution matrices created by
nucleotideSubstitutionMatrix can be used for multiple
alignments of nucleotide sequences, but must be
completed with gap penalty rows and columns (see example below).
If the consensus matrix of a multiple alignment of nucleotide sequences contains rows labeled ‘+’ and/or ‘.’, these rows are ignored.
The parameter gapVsGap can be used to control how
pairs of gaps are scored. If gapVsGap=NULL (default), the
corresponding diagonal entry of the substitution matrix is used as is.
In the BLOSUM matrices, this is usually a positive value, which may
not make sense under all circumstances. Therefore, the parameter
gapVsGap can be set to an alternative value, e.g. 0 for
ignoring gap-gap pairs.
The method, in any case, returns a vector of scores that is as long
as the alignment/consensus matrix has columns. The names of the vector
entries are the corresponding positions of the consensus sequence of
the alignment. How this consensus sequence is computed, can be
controlled with additional arguments that are passed on to the
msaConsensusSequence method.
The function returns a vector as long as the alignment/consensus matrix has columns. The vector is named with the consensus sequence (see details above).
Ulrich Bodenhofer
Bodenhofer, U., Bonatesta, E., Horejs-Kainrath, C., and Hochreiter, S. (2015). msa: an R package for multiple sequence alignment. Bioinformatics 31(24):3997-3999. DOI: doi:10.1093/bioinformatics/btv494.
msa, MsaAAMultipleAlignment,
MsaDNAMultipleAlignment,
MsaRNAMultipleAlignment,
MsaMetaData,
MultipleAlignment,
msaConsensusSequence
## load 'pwalign' package which provides substitution matrices library(pwalign) ## read sequences filepath <- system.file("examples", "HemoglobinAA.fasta", package="msa") mySeqs <- readAAStringSet(filepath) ## perform multiple alignment myAlignment <- msa(mySeqs) ## compute consensus scores using the BLOSUM62 matrix data(BLOSUM62) msaConservationScore(myAlignment, BLOSUM62) ## compute consensus scores using the BLOSUM62 matrix ## without scoring gap-gap pairs and using a different consensus sequence msaConservationScore(myAlignment, BLOSUM62, gapVsGap=0, type="upperlower") ## compute a consensus matrix first conMat <- consensusMatrix(myAlignment) data(PAM250) msaConservationScore(conMat, PAM250, gapVsGap=0) ## DNA example filepath <- system.file("examples", "exampleDNA.fasta", package="msa") mySeqs <- readDNAStringSet(filepath) ## perform multiple alignment myAlignment <- msa(mySeqs) ## create substitution matrix with gap penalty -8 mat <- nucleotideSubstitutionMatrix(4, -1) mat <- cbind(rbind(mat, "-"=-8), "-"=-8) ## compute consensus scores using this matrix msaConservationScore(myAlignment, mat, gapVsGap=0)## load 'pwalign' package which provides substitution matrices library(pwalign) ## read sequences filepath <- system.file("examples", "HemoglobinAA.fasta", package="msa") mySeqs <- readAAStringSet(filepath) ## perform multiple alignment myAlignment <- msa(mySeqs) ## compute consensus scores using the BLOSUM62 matrix data(BLOSUM62) msaConservationScore(myAlignment, BLOSUM62) ## compute consensus scores using the BLOSUM62 matrix ## without scoring gap-gap pairs and using a different consensus sequence msaConservationScore(myAlignment, BLOSUM62, gapVsGap=0, type="upperlower") ## compute a consensus matrix first conMat <- consensusMatrix(myAlignment) data(PAM250) msaConservationScore(conMat, PAM250, gapVsGap=0) ## DNA example filepath <- system.file("examples", "exampleDNA.fasta", package="msa") mySeqs <- readDNAStringSet(filepath) ## perform multiple alignment myAlignment <- msa(mySeqs) ## create substitution matrix with gap penalty -8 mat <- nucleotideSubstitutionMatrix(4, -1) mat <- cbind(rbind(mat, "-"=-8), "-"=-8) ## compute consensus scores using this matrix msaConservationScore(myAlignment, mat, gapVsGap=0)
This function converts a multiple sequence alignment object to formats used in other sequence analysis packages.
msaConvert(x, type=c("seqinr::alignment", "bios2mds::align", "ape::AAbin", "ape::DNAbin", "phangorn::phyDat", "bio3d::fasta"))msaConvert(x, type=c("seqinr::alignment", "bios2mds::align", "ape::AAbin", "ape::DNAbin", "phangorn::phyDat", "bio3d::fasta"))
x |
an object of class |
type |
a character string specifying to which type of object
|
The function converts x to the class of object as
specified by the type argument. The values possible
for the type argument follow the same principle
pkg::cl, i.e. x is converted to class
cl as defined in the pkg package.
The conversions for usage by the packages seqinr,
bios2mds, and ape work independently of these
packages and do not strictly require these packages. They
need not even be installed. This approach has been chosen
to avoid abundant dependencies and possible incompatibilities.
That is also why the standard S3/S4 mechanism of
as/as.class functions is not used.
The conversion to the phyDat class can be done
easily using the as.phyDat function from the
phangorn package. The msaConvert function
still provides this conversion for the sake of consistency.
However, this conversion is just a wrapper function around
the as.phyDat function from the phangorn
package. Thus, the phangorn package needs to be installed.
The conversion "ape::AAbin"
only works for multiple alignments of amino acid sequences,
while the conversions "ape::DNAbin" and
"phangorn::phyDat" only work for multiple alignments
of DNA sequences. When converting to "ape::AAbin",
gaps/dashes are replaced by ‘X’. Moreover, conversions
to "ape::DNAbin" also convert all characters to
lowercase and replace gaps/dashes by ‘n’.
The function returns an object of the class as specified by
the type argument.
Ulrich Bodenhofer
Bodenhofer, U., Bonatesta, E., Horejs-Kainrath, C., and Hochreiter, S. (2015). msa: an R package for multiple sequence alignment. Bioinformatics 31(24):3997-3999. DOI: doi:10.1093/bioinformatics/btv494.
msa, MsaAAMultipleAlignment,
MsaDNAMultipleAlignment,
MsaRNAMultipleAlignment,
MsaMetaData
## read sequences filepath <- system.file("examples", "exampleAA.fasta", package="msa") mySeqs <- readAAStringSet(filepath) ## perform multiple alignment myAlignment <- msa(mySeqs) ## convert to an object of class 'alignment' (package 'seqinr') msaConvert(myAlignment, "seqinr::alignment") ## convert to an object of class 'align' (package 'bios2mds') msaConvert(myAlignment, "bios2mds::align")## read sequences filepath <- system.file("examples", "exampleAA.fasta", package="msa") mySeqs <- readAAStringSet(filepath) ## perform multiple alignment myAlignment <- msa(mySeqs) ## convert to an object of class 'alignment' (package 'seqinr') msaConvert(myAlignment, "seqinr::alignment") ## convert to an object of class 'align' (package 'bios2mds') msaConvert(myAlignment, "bios2mds::align")
MsaMetaData
S4 class for storing metadata about multiple sequence alignment results
Objects of this virtual class are not be created and used directly. This
is an auxiliary class used by the classes
MsaAAMultipleAlignment,
MsaDNAMultipleAlignment, and
MsaRNAMultipleAlignment
The following slots are defined for MsaMetaData objects:
version:slot in which information is stored with which algorithm the multiple alignment has been computed along with its version number.
params:list in which the parameters are stored with which the multiple alignment algorithm has been executed.
call:the matched call with which the object was created
version(object):accessor to the version slot
params(x):accessor to the params slot
Enrico Bonatesta and Christoph Kainrath
Bodenhofer, U., Bonatesta, E., Horejs-Kainrath, C., and Hochreiter, S. (2015). msa: an R package for multiple sequence alignment. Bioinformatics 31(24):3997-3999. DOI: doi:10.1093/bioinformatics/btv494.
msa, msaClustalW,
msaClustalOmega, msaMuscle,
MsaAAMultipleAlignment,
MsaDNAMultipleAlignment,
MsaRNAMultipleAlignment
## read sequences filepath <- system.file("examples", "exampleAA.fasta", package="msa") mySeqs <- readAAStringSet(filepath) ## simple call with default values myAlignment <- msaClustalOmega(mySeqs) ## show the algorithm version with which the results were created version(myAlignment) ## show the results show(myAlignment) ## print the results print(myAlignment, show="alignment") print(myAlignment, show=c("alignment", "version")) print(myAlignment, show="standardParams") print(myAlignment, show="algParams") print(myAlignment, show=c("call", "version")) ## show the params params(myAlignment)## read sequences filepath <- system.file("examples", "exampleAA.fasta", package="msa") mySeqs <- readAAStringSet(filepath) ## simple call with default values myAlignment <- msaClustalOmega(mySeqs) ## show the algorithm version with which the results were created version(myAlignment) ## show the results show(myAlignment) ## print the results print(myAlignment, show="alignment") print(myAlignment, show=c("alignment", "version")) print(myAlignment, show="standardParams") print(myAlignment, show="algParams") print(myAlignment, show=c("call", "version")) ## show the params params(myAlignment)
MsaAAMultipleAlignment,
MsaDNAMultipleAlignment, and MsaRNAMultipleAlignment
S4 classes for storing multiple alignments of amino acid, DNA, and RNA sequences along with algorithm metadata
Objects of these classes are returned by the multiple sequence
alignment algorithms msaClustalW,
msaClustalOmega, msaMuscle, and the
wrapper function msa, all of which are
provided by the msa package.
The class MsaAAMultipleAlignment extends the
AAMultipleAlignment class, the class
MsaDNAMultipleAlignment extends the
DNAMultipleAlignment class, and the class
MsaRNAMultipleAlignment extends the
RNAMultipleAlignment class. All three classes
extend their parent classes by the slots contained in the
MsaMetaData, i.e. all three classes are class
unions of the aforementioned parent classes and the class
MsaMetaData.
print(x, show=c("alignment", "version", "call"),
showNames=TRUE, showConsensus=TRUE, halfNrow=9, nameWidth=20, ...):prints information about the object x; the show
argument allows for determining what should be printed.
The show must be a character vector and may contain any
combination of the following strings:
if show contains "alignment", the multiple
sequence alignment is printed in a way similar to the
corresponding method from the Biostrings package
(except for the consensus sequence, see below).
If show contains "complete", the entire width of
the alignment is printed by splitting it over multiple blocks of
lines if necessary. This overrules "alignment" if both
are contained in the show argument.
If show contains "version",
the version slot is shown. If show contains
"call", the call slot is shown.
If show contains "standardParams", the
settings of the parameters that are common to all three
multiple sequence alignment algorithms are shown. If show
contains "algParams", the
algorithm-specific parameters are shown.
The order in which the strings are placed in the show
argument does not have an effect on the order in which
data are printed. The default is
show=c("alignment", "version", "call"), i.e. by default,
the multiple sequence alignment is shown along with version and
call information. If show contains "all", the
complete alignment is shown along with version information,
call, and the complete set of parameters.
As said above, by default, printing alignments is similar to
the standard print method provided by the Biostrings
package, whereas including "complete" in the argument
show prints the entire width of the alignment.
Unlike the method from the Biostrings
package, the appearance can be customized: by default,
the consensus sequence is appended below the alignment. To switch
this off, use showConsensus=FALSE. Whether or not sequence
names should be printed can be controlled via the
showNames argument. The width reserved for the sequence
names can be adjusted using the nameWidth argument;
the default is 20 like in the Biostrings method.
If the number of sequences in the alignment is large, output
can become quite lengthy. That is why only the first
halfNrow and the last halfNrow sequences are
shown. To show all sequences, set halfNrow to NA
or -1. Note that print can also handle masked objects,
where the masked sequences/positions are shown as hash marks.
However, the consensus sequences are computed from the
complete, unmasked alignment and displayed as such.
Additional arguments are passed on to
msaConsensusSequence for customizing how the
consensus sequence is computed.
show(object):displays the alignment along with
metadata; synonymous to calling print with default
arguments.
version(object):displays the algorithm with which
the multiple alignment has been computed along with its
version number (see also MsaMetaData).
params(x):accessor to the params slot (see
also MsaMetaData)
Enrico Bonatesta, Christoph Kainrath, and Ulrich Bodenhofer
Bodenhofer, U., Bonatesta, E., Horejs-Kainrath, C., and Hochreiter, S. (2015). msa: an R package for multiple sequence alignment. Bioinformatics 31(24):3997-3999. DOI: doi:10.1093/bioinformatics/btv494.
msa, msaClustalW,
msaClustalOmega, msaMuscle,
MsaMetaData
## read sequences filepath <- system.file("examples", "exampleAA.fasta", package="msa") mySeqs <- readAAStringSet(filepath) ## simple call with default values myAlignment <- msaClustalOmega(mySeqs) ## show the algorithm version with which the results were created version(myAlignment) ## show the results show(myAlignment) ## print the results print(myAlignment, show="alignment") print(myAlignment, show="alignment", showConsensus=FALSE) print(myAlignment, show=c("alignment", "version")) print(myAlignment, show="standardParams") print(myAlignment, show="algParams") print(myAlignment, show=c("call", "version")) ## print results with custom consensus sequence print(myAlignment, show="complete", type="upperlower", thresh=c(50, 20)) ## show the params params(myAlignment)## read sequences filepath <- system.file("examples", "exampleAA.fasta", package="msa") mySeqs <- readAAStringSet(filepath) ## simple call with default values myAlignment <- msaClustalOmega(mySeqs) ## show the algorithm version with which the results were created version(myAlignment) ## show the results show(myAlignment) ## print the results print(myAlignment, show="alignment") print(myAlignment, show="alignment", showConsensus=FALSE) print(myAlignment, show=c("alignment", "version")) print(myAlignment, show="standardParams") print(myAlignment, show="algParams") print(myAlignment, show=c("call", "version")) ## print results with custom consensus sequence print(myAlignment, show="complete", type="upperlower", thresh=c(50, 20)) ## show the params params(myAlignment)
This function calls the multiple sequence alignment algorithm MUSCLE.
msaMuscle(inputSeqs, cluster="default", gapOpening="default", gapExtension="default", maxiters="default", substitutionMatrix="default", type="default", order=c("aligned", "input"), verbose=FALSE, help=FALSE, ...)msaMuscle(inputSeqs, cluster="default", gapOpening="default", gapExtension="default", maxiters="default", substitutionMatrix="default", type="default", order=c("aligned", "input"), verbose=FALSE, help=FALSE, ...)
inputSeqs |
input sequences; see |
cluster |
The clustering method which should be used.
Possible values are |
gapOpening |
gap opening penalty; the default
is 400 for DNA sequences and 420 for RNA sequences. The default
for amino acid sequences depends on the profile score settings:
for the setting |
gapExtension |
gap extension penalty; the default is 0. |
maxiters |
maximum number of iterations; the default is 16.
In the original MUSCLE implementation, it is also possible
to set |
substitutionMatrix |
substitution matrix for scoring matches and
mismatches; can be a real matrix or a file name
If the file interface is used, matrices have to be in NCBI-format.
The original MUSCLE implementation also accepts matrices in WU_BLAST
(AB_BLAST) format, but, due to copyright restrictions,
this format is not supported by |
type |
type of the input sequences |
order |
how the sequences should be ordered in the output object
(see |
verbose |
if |
help |
if |
... |
further parameters specific to MUSCLE;
An overview of parameters that are available in this interface
is shown when calling |
This is a function providing the MUSCLE multiple alignment
algorithm as an R function. It can be used for various types of
sequence data (see inputSeqs argument above). Parameters that
are common to all multiple sequences alignments provided by the
msa package are explicitly provided by the function and named
in the same for all algorithms. Most other parameters that are
specific to MUSCLE can be passed to MUSCLE via additional
arguments (see argument help above).
For a note on the order of output sequences and direct reading from
FASTA files, see msa.
Depending on the type of sequences for which it was called,
msaMuscle returns a MsaAAMultipleAlignment,
MsaDNAMultipleAlignment, or
MsaRNAMultipleAlignment object.
If called with help=TRUE, msaMuscle returns
an invisible NULL.
Enrico Bonatesta and Christoph Kainrath
Bodenhofer, U., Bonatesta, E., Horejs-Kainrath, C., and Hochreiter, S. (2015). msa: an R package for multiple sequence alignment. Bioinformatics 31(24):3997-3999. DOI: doi:10.1093/bioinformatics/btv494.
http://www.drive5.com/muscle/muscle.html
Edgar, R. C. (2004) MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 32(5):1792-1797. DOI: doi:10.1093/nar/gkh340.
Edgar, R. C. (2004) MUSCLE: a multiple sequence alignment method with reduced time and space complexity. BMC Bioinformatics 5:113. DOI: doi:10.1186/1471-2105-5-113.
msa, MsaAAMultipleAlignment,
MsaDNAMultipleAlignment,
MsaRNAMultipleAlignment,
MsaMetaData
## load 'pwalign' package which provides substitution matrices library(pwalign) ## read sequences filepath <- system.file("examples", "exampleAA.fasta", package="msa") mySeqs <- readAAStringSet(filepath) ## call msaMuscle with default values msaMuscle(mySeqs) ## call msaMuscle with custom parameters msaMuscle(mySeqs, gapOpening=12, gapExtension=3, maxiters=16, cluster="upgmamax", SUEFF=0.4, brenner=FALSE, order="input", verbose=FALSE) ## call msaMuscle with a custom substitution matrix data(PAM120) msaMuscle(mySeqs, substitutionMatrix=PAM120)## load 'pwalign' package which provides substitution matrices library(pwalign) ## read sequences filepath <- system.file("examples", "exampleAA.fasta", package="msa") mySeqs <- readAAStringSet(filepath) ## call msaMuscle with default values msaMuscle(mySeqs) ## call msaMuscle with custom parameters msaMuscle(mySeqs, gapOpening=12, gapExtension=3, maxiters=16, cluster="upgmamax", SUEFF=0.4, brenner=FALSE, order="input", verbose=FALSE) ## call msaMuscle with a custom substitution matrix data(PAM120) msaMuscle(mySeqs, substitutionMatrix=PAM120)
The msaPrettyPrint function provides an R interface to the
powerful LaTeX package texshade.sty which allows for a
highly customizable plots of multiple sequence alignments.
msaPrettyPrint(x, y, output=c("pdf", "tex", "dvi", "asis"), subset=NULL, file=NULL, alFile=NULL, askForOverwrite=TRUE, psFonts=FALSE, code=NA, paperWidth=11, paperHeight=8.5, margins=c(0.1, 0.3), shadingMode=c("identical", "similar", "functional"), shadingModeArg=NA, shadingColors=c("blues", "reds", "greens", "grays", "black"), showConsensus=c("bottom", "top", "none"), consensusColors=c("ColdHot", "HotCold", "BlueRed", "RedBlue", "GreenRed", "RedGreen", "Gray"), consensusThreshold=50, showLogo=c("top", "bottom", "none"), logoColors=c("chemical", "rasmol", "hydropathy", "structure", "standard area", "accessible area"), showLogoScale=c("none", "leftright", "left", "right"), showNames=c("left", "right", "none"), showNumbering=c("right", "left", "none"), showLegend=TRUE, furtherCode=NA, verbose=FALSE, index=TRUE)msaPrettyPrint(x, y, output=c("pdf", "tex", "dvi", "asis"), subset=NULL, file=NULL, alFile=NULL, askForOverwrite=TRUE, psFonts=FALSE, code=NA, paperWidth=11, paperHeight=8.5, margins=c(0.1, 0.3), shadingMode=c("identical", "similar", "functional"), shadingModeArg=NA, shadingColors=c("blues", "reds", "greens", "grays", "black"), showConsensus=c("bottom", "top", "none"), consensusColors=c("ColdHot", "HotCold", "BlueRed", "RedBlue", "GreenRed", "RedGreen", "Gray"), consensusThreshold=50, showLogo=c("top", "bottom", "none"), logoColors=c("chemical", "rasmol", "hydropathy", "structure", "standard area", "accessible area"), showLogoScale=c("none", "leftright", "left", "right"), showNames=c("left", "right", "none"), showNumbering=c("right", "left", "none"), showLegend=TRUE, furtherCode=NA, verbose=FALSE, index=TRUE)
x |
an object of class |
y |
argument for restricting the output to a subset of columns;
can be a numeric vector of length 2 with a lower and an upper bound
or an object of class |
output |
type of output to be generated (see details below) |
subset |
can be used to specify a subset of sequences in the
multiple alignment |
file |
name of output file; if no name
is given, the name of the output file defaults to name of the
object provided as argument |
alFile |
name of alignment file to be created;
|
askForOverwrite |
if |
psFonts |
if |
code |
this argument can be used to specify the entire LaTeX code
in the |
paperWidth, paperHeight
|
paper format to be used in the resulting
document; defaults to 11in x 8.5in (US letter in landscape
orientation). Ignored for |
margins |
a numeric vector of length 2 with the horizontal and vertical margins, respectively; the default is 0.1in for the horizontal and 0.3in for the vertical margin. |
shadingMode |
shading mode; currently the shading modes
|
shadingModeArg |
for shading modes |
shadingColors |
color scheme for shading; valid
|
showConsensus |
where to show the consensus sequence;
possible values are |
consensusColors |
color scheme for printing the consensus
sequence; the following choices are possible: |
consensusThreshold |
one or two numbers between 0 and 100, where the second one is optional and must be larger than the first one (see documentation of texshade.sty for details) |
showLogo |
where to show a sequence logo;
possible values are |
logoColors |
color scheme for printing the sequence logo;
the following choices are possible: |
showLogoScale |
where to plot the vertical axis of the
sequence logo; possible values are |
showNames |
where to print sequence names;
possible values are |
showNumbering |
where to print sequence numbers;
possible values are |
showLegend |
if |
furtherCode |
additional LaTeX code to be included in the
|
verbose |
if |
index |
argument to be forwarded to |
The msaPrettyPrint function writes a multiple alignment
to a .fasta file and creates LaTeX code for
pretty-printing the multiple alignment on the basis of the
LaTeX package texshade.sty. If output="asis",
msaPrettyPrint prints a LaTeX fragment consisting of the
texshade environment to the console. The parameters described
above can be used to customize the way the multiple alignment is
formatted. If output="tex", a complete LaTeX file including
preamble is created. For output="dvi" and output="pdf",
the same kind of LaTeX file is created, but processed using (PDF)LaTeX
to produce a final DVI or PDF file, respectively. The file
argument be used to determine the file name of the final output file
(except for the output="asis" which does not create an output
file).
The choice output="asis" is particularly useful for Sweave or
knitr documents. If msaPrettyPrint is called with
output="asis" in a code chunk with results="tex"
(Sweave) or results="asis" (knitr), then the resulting LaTeX
fragment consisting of the texshade environment is directly
included in the LaTeX document that is created from the Sweave/knitr
document.
As noted above, if they are not specified explicitly, output file
names are determined automatically. It is important to point out that
all file names need to be LaTeX-compliant, i.e. no special characters
and spaces (!) are allowed. If a file name would be invalid,
msaPrettyPrint makes a default choice.
Moreover, if sequence names are to be printed, there might be names
that are not LaTeX-compliant and lead to LaTeX errors. In order
to check that in advance, the function msaCheckNames
is available.
Note that texi2dvi and texi2pdf always
save the resulting DVI/PDF files to the current working directory,
even if the LaTeX source file is in a different directory.
That is also the reason why the temporary file is created in the
current working directory in the example below.
msaPrettyPrint returns an invisible character vector consisting
of the LaTeX fragment with the texshade environment.
Ulrich Bodenhofer, Enrico Bonatesta, and Christoph Kainrath
Bodenhofer, U., Bonatesta, E., Horejs-Kainrath, C., and Hochreiter, S. (2015). msa: an R package for multiple sequence alignment. Bioinformatics 31(24):3997-3999. DOI: doi:10.1093/bioinformatics/btv494.
https://www.ctan.org/pkg/texshade
Beitz, E. (2000). TeXshade: shading and labeling of multiple sequence alignments using LaTeX2e. Bioinformatics 16(2):135-139. DOI: doi:10.1093/bioinformatics/16.2.135.
## read sequences filepath <- system.file("examples", "exampleAA.fasta", package="msa") mySeqs <- readAAStringSet(filepath) ## call unified interface msa() for default method (ClustalW) and ## default parameters myAlignment <- msa(mySeqs) ## show resulting LaTeX code with default settings msaPrettyPrint(myAlignment, output="asis", askForOverwrite=FALSE) ## create PDF file according to some custom settings ## Not run: tmpFile <- tempfile(pattern="msa", tmpdir=".", fileext=".pdf") tmpFile msaPrettyPrint(myAlignment, file=tmpFile, output="pdf", showNames="left", showNumbering="none", showLogo="top", showConsensus="bottom", logoColors="rasmol", verbose=FALSE, askForOverwrite=FALSE) library(Biobase) openPDF(tmpFile) ## End(Not run)## read sequences filepath <- system.file("examples", "exampleAA.fasta", package="msa") mySeqs <- readAAStringSet(filepath) ## call unified interface msa() for default method (ClustalW) and ## default parameters myAlignment <- msa(mySeqs) ## show resulting LaTeX code with default settings msaPrettyPrint(myAlignment, output="asis", askForOverwrite=FALSE) ## create PDF file according to some custom settings ## Not run: tmpFile <- tempfile(pattern="msa", tmpdir=".", fileext=".pdf") tmpFile msaPrettyPrint(myAlignment, file=tmpFile, output="pdf", showNames="left", showNumbering="none", showLogo="top", showConsensus="bottom", logoColors="rasmol", verbose=FALSE, askForOverwrite=FALSE) library(Biobase) openPDF(tmpFile) ## End(Not run)