detectMotifs: Detect over-represented motifs

Description Usage Arguments Details Value Author(s)

Description

Detect over-represented motifs

Usage

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detectMotifs(fg.seqs, bg.seqs, fg.genes = NULL, bg.genes = NULL,
  method = c("cvp", "all")[1], min.seqs = 5, max.pvalue = 1e-06,
  max.gw.pvalue = NULL, center = "STY", ncores = 1, verbose = TRUE,
  annotate = FALSE)

Arguments

fg.seqs

a character vector of foreground sequences

bg.seqs

a character vector of background sequences

fg.genes

character vector of gene names of foreground sequences, it should have the same length as fg.seqs

bg.genes

character vector of gene names of background sequences, it should have the same length as bg.seqs

method

the algorithm used to detect potential motifs, multiple are allowed

min.seqs

the minimum frequency of a motif should be considered

max.pvalue

the maximum FDR to be reported

max.gw.pvalue

the maximum p value of on gene wise to be reported, only useful when both fg.genes and bg.genes are specified

center

the amino acid centered at the sequences, sequences with other center AA would be removed from the list. To disable this function, set center = NULL. Only used in checkSeqs and motif_all.

ncores

the number of cores to be used, passed to mclapply.

verbose

logical, whether print message

annotate

whether the discovered motif should be annotated by known motifs

Details

more details here

Value

a data.frame of the over-representation data analysis

Author(s)

Chen Meng


mengchen18/PTMotif documentation built on May 29, 2019, 6:53 p.m.