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Extract pwm of sequences from a motif database

extract_pwm.Rd

Extracts the pwm of a motif from a motif database. extract_pwm_old is a deprecated version of this function, which is slower, and returns slightly different results due to float percision instead of double. If the sequences are not of the same length, the old version will be used.

Usage

extract_pwm_old(
  sequences,
  motifs = NULL,
  dataset = all_motif_datasets(),
  spat = NULL,
  spat_min = 0,
  spat_max = NULL,
  bidirect = TRUE,
  prior = 0.01,
  func = "logSumExp",
  parallel = getOption("prego.parallel", TRUE)
)

extract_pwm(
  sequences,
  motifs = NULL,
  dataset = MOTIF_DB,
  spat = NULL,
  spat_min = 0,
  spat_max = NULL,
  bidirect = TRUE,
  prior = 0.01,
  func = "logSumExp",
  parallel = getOption("prego.parallel", TRUE)
)

Arguments

sequences

a vector of sequences

motifs

names of specific motifs to extract from the dataset

dataset

a data frame with PSSMs ('A', 'C', 'G' and 'T' columns), with an additional column 'motif' containing the motif name, for example HOMER_motifs or JASPAR_motifs, or all_motif_datasets(), or a MotifDB object.

spat

a data frame with the spatial model (as returned from the $spat slot from the regression). Should contain a column called 'bin' and a column called 'spat_factor'.

spat_min

the minimum position to use from the sequences. The default is 1.

spat_max

the maximum position to use from the sequences. The default is the length of the sequences.

bidirect

is the motif bi-directional. If TRUE, the reverse-complement of the motif will be used as well.

prior

a prior probability for each nucleotide.

func

the function to use to combine the PWMs for each sequence. Either 'logSumExp' or 'max'. The default is 'logSumExp'.

parallel

logical, whether to use parallel processing

Value

a matrix size of # of sequences x # of motifs with the pwm of each sequence for each motif

Examples

if (FALSE) { # \dontrun{
pwms <- extract_pwm(
    cluster_sequences_example,
    motifs = c("JASPAR.CDX1", "HOMER.Hnf1", "HOMER.GATA3_2")
)
head(pwms)

# all motifs
all_pwms <- extract_pwm(cluster_sequences_example, prior = 0.01)
dim(all_pwms)
all_pwms[1:5, 1:5]

# for a specific dataset
pwms_jaspar <- extract_pwm(cluster_sequences_example, dataset = JASPAR_motifs, prior = 0.01)
head(pwms_jaspar)

# for specific motifs
pwms_jaspar <- extract_pwm(
    cluster_sequences_example,
    motifs = c("JASPAR.CDX1", "JASPAR.CDX2"),
    prior = 0.01
)
} # }