random.msa: Random Alignment
In bios2mds: From Biological Sequences to Multidimensional Scaling

Description Usage Arguments Details Value Note Author(s) References See Also Examples

Builds a multiple sequence alignment (MSA) of random sequences.

1 2	random.msa(nb.seq = 100, id = "SEQ", nb.pos = 100, gap = FALSE, aa.strict = FALSE, align = NULL, align.replace = TRUE)

`nb.seq`	a numeric value indicating the number of sequences in the random MSA. Default is 100.
`id`	a string of characters used to tag each sequence name. Default is "SEQ". An incremented number is attached to this tag to name each sequence.
`nb.pos`	a numeric value indicating the length of each sequence in the random MSA. Default is 100.
`gap`	a logical value indicating whether the gap character should be considered as a supplementary symbol (TRUE) or not (FALSE). Default is FALSE.
`aa.strict`	a logical value indicating whether only strict amino acids should be taken into account (TRUE) or not (FALSE). Default is FALSE.
`align`	an object of class 'align', obtained from `import.fasta` or `import.msf` function. If this parameter is not NULL, the composition of the output sequences is based on the composition of the input sequences. Default is NULL.
`align.replace`	a logical value indicating random drawing with replacement (TRUE) or without replacement (FALSE) of characters present in `align`. Default is FALSE.

random.msa may be used to compare a reference MSA to a random MSA. The random MSA must have the same characteristics as the reference MSA (same number of sequences of same length).

A mmds procedure can be applied to the random MSA to assess the amount of variance due to random mutations in the reference MSA.

A named list whose objects correspond to random sequences.

The subset function is used for random selection of the amino acids. If a truly random procedure is needed, see random package.

Julien Pele

For an application of random MSA see :

Pele J, Abdi H, Moreau M, Thybert D and Chabbert M (2011) Multidimensional scaling reveals the main evolutionary pathways of class A G-protein-coupled receptors. PLoS ONE 6: e19094. doi:10.1371.

permutation and synsequence functions from seqinr package.

# generating a random sequence alignment with the same characterics
# as human GPCRs:
aln <- import.fasta(system.file("msa/human_gpcr.fa", package = "bios2mds"))
nb.seq <- length(aln)
nb.pos <- length(aln[[1]])
aln.random <- random.msa(nb.seq = nb.seq, nb.pos = nb.pos)

Loading required package: amap
Loading required package: e1071
Loading required package: scales
Loading required package: cluster
Loading required package: rgl
Warning messages:
1: In rgl.init(initValue, onlyNULL) : RGL: unable to open X11 display
2: 'rgl_init' failed, running with rgl.useNULL = TRUE 
3: .onUnload failed in unloadNamespace() for 'rgl', details:
  call: fun(...)
  error: object 'rgl_quit' not found