factorFootprints: plot ATAC-seq footprints infer factor occupancy genome wide

In jianhong/ATACseqQC: ATAC-seq Quality Control

plot ATAC-seq footprints infer factor occupancy genome wide

Description

Aggregate ATAC-seq footprint for a given motif generated over binding sites within the genome.

Usage

factorFootprints(
  bamfiles,
  index = bamfiles,
  pfm,
  genome,
  min.score = "95%",
  bindingSites,
  seqlev = paste0("chr", c(1:22, "X", "Y")),
  upstream = 100,
  downstream = 100,
  maxSiteNum = 1e+06,
  anchor = "cut site",
  group = "strand",
  ...
)

Arguments

bamfiles	A vector of characters indicates the file names of bams. All the bamfiles will be pulled together.
index	The names of the index file of the 'BAM' file being processed; This is given without the '.bai' extension.
pfm	A Position frequency Matrix represented as a numeric matrix with row names A, C, G and T.
genome	An object of BSgenome.
min.score	The minimum score for counting a match. Can be given as a character string containing a percentage (e.g. "95 score or as a single number. See matchPWM.
bindingSites	A object of GRanges indicates candidate binding sites (eg. the output of fimo). The GRanges object must have score column in the metadata column.
seqlev	A vector of characters indicates the sequence levels.
upstream, downstream	numeric(1) or integer(1). Upstream and downstream of the binding region for aggregate ATAC-seq footprint.
maxSiteNum	numeric(1). Maximal number of predicted binding sites. if predicted binding sites is more than this number, top maxSiteNum binding sites will be used.
anchor	"cut site" or "fragment center". If "fragment center" is used, the input bamfiles must be paired-end.
group	Group information for the bamfiles. Default by strand. Otherwise, a factor or vector of characters with same length of bamfiles. The group is limited to 2 groups.
...	xlab, legTitle, xlim or ylim could be used by plotFootprints

Value

an invisible list of matrixes with the signals for plot. It includes: - signal mean values of coverage for positive strand and negative strand in feature regions - spearman.correlation spearman correlations of cleavage counts in the highest 10-nucleotide-window and binding prediction score. - bindingSites predicted binding sites.

Author(s)

Jianhong Ou, Julie Zhu

References

Chen, K., Xi, Y., Pan, X., Li, Z., Kaestner, K., Tyler, J., Dent, S., He, X. and Li, W., 2013. DANPOS: dynamic analysis of nucleosome position and occupancy by sequencing. Genome research, 23(2), pp.341-351.

Examples

bamfile <- system.file("extdata", "GL1.bam",
                       package="ATACseqQC")
library(MotifDb)
CTCF <- query(MotifDb, c("CTCF"))
CTCF <- as.list(CTCF)
library(BSgenome.Hsapiens.UCSC.hg19)
factorFootprints(bamfile, pfm=CTCF[[1]],
                genome=Hsapiens,
                min.score="95%", seqlev="chr1",
                upstream=100, downstream=100)
##### Using user defined binding sites #####
bds <- readRDS(system.file("extdata", "jolma2013.motifs.bindingList.95.rds",
                          package="ATACseqQC"))
bindingSites <- bds[["Hsapiens-jolma2013-CTCF"]]
seqlev <- "chr1" #seqlevels(bindingSites)
ff <- factorFootprints(bamfile, pfm=CTCF[[1]],
                bindingSites=bindingSites,
                seqlev=seqlev,
                upstream=100, downstream=100)
##### normalize the plot by distal signals #####
library(motifStack)
Profile <- lapply(ff$signal, function(.ele) colMeans(.ele, na.rm = TRUE))
pfm <- new('pfm', mat=as.matrix(CTCF[[1]]), name='CTCF')
plotFootprints(Profile=c(Profile[["+"]], Profile[["-"]]),
              Mlen=ff$Mlen,
              motif=pfm,
              segmentation=ff$Profile.segmentation,
              reNormalizeByDistalSig=TRUE)

jianhong/ATACseqQC documentation built on Nov. 2, 2024, 12:08 a.m.