makePromoterDBfromRE: makePromoterDBfromRE

In jsalojar/TFbindR: Identification and Counting of the Occurence of Motifs in a Set of Promoter Sequences. Motif Enrichment Analysis

Description

Identify and count the occurence of sequence motifs, described by regular expressions, in a set of promoter sequences. Both, sense and antisense strands are scanned for the occurence of each motif and the number of matches is reported.

Usage

makePromoterDBfromRE(Motifs, promoter.fasta, promoterDB = "promoter.DB")

Arguments

Motifs	a character vector of the motifs to be matched. A motif can be defined with the full sequences or with special characters.
promoter.fasta	Fasta file of the promoter sequences.
promoterDB	Output file where the results will be saved.

Value

A list names Strands with 3 elements,

plus	A count matrix of the occurence of motifs in the "minus" strand.
minus	A count matrix of the occurence of motifs in the "plus" strand.
both	A count matrix of the occurence of motifs in the "minus" and "plus" strands together.

Examples

# Read a file of sample sequence motifs.
motifs.dir = system.file("extdata", "AGRIS_PLACE_motifs_short_mb2.txt", package="TFbindR", mustWork = TRUE)
Motifs=read.delim(file = motifs.dir ,header=TRUE, sep="\t", as.is=T)

# Remove duplicated motifs.
Motifs=Motifs[which(!duplicated(Motifs$Motif)),]

# Read a sample fasta file. 
promoter.dir = system.file("extdata","TAIR10_upstream_1000_translation_start_20101028.fa",package="TFbindR")

# Specify the output directory.
output.dir="."

# Run the function to create the DB and save it into R file type .rda which is automatically compressed
makePromoterDBfromRE(Motifs = Motifs$Motif,promoter.fasta = promoter.dir, promoterDB=file.path(output.dir,"TAIR10_500bp_upstream.RE.db.rda"))

jsalojar/TFbindR documentation built on Dec. 9, 2019, 12:16 a.m.