findMotif {motifRG} | R Documentation |
The function searches motifs that discriminate the given foregound and background sequences.
findMotif(all.seq, category, weights = rep(1, length(all.seq)), start.width=6,min.cutoff=5, min.ratio=1.3, min.frac=0.01, both.strand=TRUE, flank=2, max.motif=5, mask=TRUE,other.data=NULL, start.nmer=NULL, enriched.only=F,n.bootstrap = 5, bootstrap.pvalue=0.1,is.parallel = TRUE,mc.cores = 4,min.info=10,max.width=15,discretize=TRUE)
all.seq |
DNAStringSet; foreground and background sequences. |
category |
numeric vector; specify which sequences are foreground (with value 1), and background (value 0). |
weights |
numeric vector: the weights for all sequences. Default: 1 |
start.width |
logical; the width for enumerating seed patterns |
min.cutoff |
numeric; the score cutoff required for seed selection. All scores are negative, the lower the better. |
min.ratio |
numeric; the minimum fold change of motif occurences in foreground vs background. |
min.frac |
numeric; the minimum fraction of fg/bg sequences containing the candidate motifs |
both.strand |
logical; if true, search both strands |
flank |
integer; the length for step-wise pattern extension at both ends on candidate motifs |
max.motif |
integer; the maximum number of output motifs |
mask |
logical; if true, mask previous motifs when searching for the next motif |
other.data |
if not NULL, a matrix with additional terms for the regression model for bias adjustment |
start.nmer |
if not NULL, a matrix with counts for user specified seed pattern in each sequence |
enriched.only |
logical; if true, only predict enriched motif |
n.bootstrap |
integer; the number of bootstrapping tests to estimate score variance |
bootstrap.pvalue |
numeric: the bootstrap t.test pvalues to determine the significance of improvement |
is.parallel |
logical;if true, runs in parallel mode, and requires "parallel" library |
mc.cores |
integer; the number of CPUs for paralel run |
min.info |
minimal information content for the motif to prevent it from being too degenerate |
max.width |
maximum width of the motif for extension |
discretize |
|
return a list with following elements:
motifs |
a list motif descriptions of class Motif-class |
.
category |
input binary specification of foreground/background |
mask.motifs |
if |
MD.peak.seq <- readDNAStringSet(system.file("extdata","MD.peak.fa", package="motifRG")) MD.control.seq <- readDNAStringSet(system.file("extdata","MD.control.fa", package="motifRG")) category <- c(rep(1, length(MD.peak.seq)), rep(0, length(MD.control.seq))) MD.motifs <- findMotif(append(MD.peak.seq, MD.control.seq),category, max.motif=3,enriched=TRUE) ### Get summary of motifs summaryMotif(MD.motifs$motifs, MD.motifs$category) ### plot the dinucleotide representation of the first motif plotMotif(MD.motifs$motifs[[1]]@match$pattern) ### Create table of motifs in Latex motifLatexTable(MD.motifs, main="MD motifs") ### Create table of motifs in Html motifHtmlTable(MD.motifs)