Simulate sequences with multiple motifs

Simulate a set of sequences incorporating multiple motifs

Usage

simMultiMotifs(
  n,
  width,
  pfm = NULL,
  bg = NULL,
  nt = c("A", "C", "G", "T"),
  prob = rep(0.25, 4),
  shape1 = 1,
  shape2 = shape1,
  rate = NA,
  theta = NA,
  as = "DNAStringSet",
  ol = c("random", "first", "last"),
  ...
)

Arguments

n

The number of sequences to simulate

width

Width of sequences to simulate

pfm

List of Probability Weight/Frequency Matrices

bg

Optional, pre-defined set of background sequences. Can be passed as an XStringSet or character vector. All sequences must be the same width

nt

Nucleotides to include

prob

Sampling probabilities for each nucleotide

shape1, shape2

Passed to rbetabinom.ab

rate

The expected rate of motifs per sequence. Is equivalent to \( \lambda \) in rpois. If set to NULL or NA, all sequences will be simulated with a single motif, otherwise a Poisson distribution will be used

theta

Overdispersion parameter passed to rnegbin. If set to NULL or NA the rate parameter will be passed to rpois. However if this value is set, the rate and theta parameters are passed to rnegbin to simulate overdispersed counts

as

ObjectClass to return objects as. Defaults to DNAStringSet, but other viable options may include 'character', 'CharacterList' or any other class from which a character vector may be coerced.

ol

When randomly simulated positions overlap, choose one either at random, by the first occurring PFM in the list of PFMs, or by the last.

...

Not used

Value

A DNAStringSet with mcols denoting the positions of all inserted motifs

Details

Simulate a set of sequences with multiple motifs inserted using different rates and distributions, as specified. All shape, rate and theta parameters are recycled to match the length of the supplied motif list, and can be supplied as vectors to tailor these parameters to each provided element of the list of matrices

Examples

data("ex_pfm")
## Simulate sequences including both ESR1 and ANDR, but with
## ESR1 being included at a higher rate
seq <- simMultiMotifs(10, 100, ex_pfm[1:2], rate = c(2, 1))
seq
#> DNAStringSet object of length 10:
#>      width seq
#>  [1]   100 GCTGCATACAAGCCCAAGTTGCTAATTGAAAGG...ACAGTACAGAGTCCCCTTTCCAAAATGTGTCCT
#>  [2]   100 GGTATTGCTTCAATGTTCTCGCCTCGTTGGTAG...CTAGGGTCAACGAATGGTCACAGTGACCCAGTA
#>  [3]   100 GATGGTCGCATTTCTGGTGATTTATGTCTCTGT...TTGTTTGTTTCAATCGGGTCATAGTGACCCTGC
#>  [4]   100 TAGTTAAGGTTAGCCTGACCCTTAGCGCTTTAT...GGAGAAATAACAATGAAGGATTTTGGACTTAGA
#>  [5]   100 AGCTGCAGCCCGTTATTTATCCTGTTTGTTCCT...AGTCATGACGCAGCGAAGGTCACCCTGAGCTCA
#>  [6]   100 TGCGCAGCATCGCGGAACACAGACTACGGGGGG...GACGGTTTTCGCTGGGAAGACCTGAGCCACGAT
#>  [7]   100 CTCGAGCTCTCATCTTTTCTGTACGACAGAATG...TATGACTGTGTAGTCAGCGTCGCCACCCATATC
#>  [8]   100 GCGGCGCATCTTGACAGACAGAGGTCATACCGT...TAACCGGCTACACCTGTCTCAGATGTTAAGTTG
#>  [9]   100 CGGAACAGCCGTGTTTTGTGCTGTTAACTTCCC...GTTAAGGGGGTGGGGCAGACTGTCCTTACGATG
#> [10]   100 CATGGGCGAAGATACGTATCGCCAGAAGTTCGG...AGCAAGGCAATCGCACACGGGTGAAGGGCCCAA
## The positions of the motifs are included in the mcols
mcols(seq)
#> DataFrame with 10 rows and 3 columns
#>             ESR1          ANDR  n_motifs
#>    <IntegerList> <IntegerList> <numeric>
#> 1          31,70         43,51         4
#> 2          71,82   4,17,18,...         6
#> 3       17,39,83      13,31,59         6
#> 4              7                       1
#> 5          37,84         13,36         4
#> 6                                      0
#> 7             78                       1
#> 8       22,43,59            53         4
#> 9             79         12,46         3
#> 10            48         27,42         3