Conduct Peak Annotation.

AnnoPeak(
  peak.df,
  species = c("Human", "Mouse", "Rat", "Fly", "Arabidopsis", "Yeast", "Zebrafish",
    "Worm", "Bovine", "Pig", "Chicken", "Rhesus", "Canine", "Xenopus", "Anopheles",
    "Chimp", "E coli strain Sakai", "Myxococcus xanthus DK 1622"),
  seq.style = c("UCSC", "NCBI", "Ensembl", "None"),
  gtf.file = NULL,
  up.dist = 3000,
  down.dist = 3000,
  ...
)

Arguments

peak.df	Dataframe contains all consensus peaks.
species	Species used, chosen from "Human","Mouse","Rat","Fly","Arabidopsis","Yeast","Zebrafish","Worm","Bovine","Pig","Chicken","Rhesus", "Canine","Xenopus","Anopheles","Chimp","E coli strain Sakai","Myxococcus xanthus DK 1622". Default: "Human".
seq.style	The style of sequence, chosen from UCSC, NCBI, Ensembl, None. This should be compatible with the genome and gtf file you used to generate count matrix and peak files. Default: "UCSC".
gtf.file	GTF file used to create TxDb object. Useful when specie you used is not available in `species`. Default: NULL.
up.dist	The upstream distance from the TSS. Default: 3000bp.
down.dist	The downstream distance from the TSS. Default: 3000bp.
...	Parameters for `annotatePeak`.

Value

List contains peak annotation dataframe and plot.

Examples

library(DEbPeak)
peak.file <- system.file("extdata", "debchip_peaks.bed", package = "DEbPeak")
peak.df <- GetConsensusPeak(peak.file = peak.file)
peak.profile <- PeakProfile(peak.df, species = "Mouse", by = "gene", region.type = "body", nbin = 800)
#> 
#> 载入程辑包：‘BiocGenerics’
#> The following objects are masked from ‘package:stats’:
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#>     IQR, mad, sd, var, xtabs
#> The following objects are masked from ‘package:base’:
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#>     anyDuplicated, append, as.data.frame, basename, cbind, colnames,
#>     dirname, do.call, duplicated, eval, evalq, Filter, Find, get, grep,
#>     grepl, intersect, is.unsorted, lapply, Map, mapply, match, mget,
#>     order, paste, pmax, pmax.int, pmin, pmin.int, Position, rank,
#>     rbind, Reduce, rownames, sapply, setdiff, sort, table, tapply,
#>     union, unique, unsplit, which.max, which.min
#> 
#> 载入程辑包：‘S4Vectors’
#> The following object is masked from ‘package:base’:
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#> Welcome to Bioconductor
#> 
#>     Vignettes contain introductory material; view with
#>     'browseVignettes()'. To cite Bioconductor, see
#>     'citation("Biobase")', and for packages 'citation("pkgname")'.
#> >> preparing promoter regions...	 2023-07-02 17时02分57秒 
#> >> preparing tag matrix...		 2023-07-02 17时02分58秒 
#> >> preparing start_site regions by ... 2023-07-02 17时02分58秒
#> >> preparing tag matrix...  2023-07-02 17时02分58秒 
#> >> generating figure...		 2023-07-02 17时03分09秒 
#> >> done...			 2023-07-02 17时03分09秒 
#> >> binning method is used...2023-07-02 17时03分09秒
#> >> preparing start_site regions by gene... 2023-07-02 17时03分09秒
#> >> preparing tag matrix by binning...  2023-07-02 17时03分09秒 
#> >> Running bootstrapping for tag matrix...		 2023-07-02 17时03分14秒 
#> >> binning method is used...2023-07-02 17时03分14秒
#> >> preparing body regions by gene... 2023-07-02 17时03分14秒
#> >> preparing tag matrix by binning...  2023-07-02 17时03分14秒 
#> >> preparing matrix with extension from (TSS-20%)~(TTS+20%)... 2023-07-02 17时03分14秒
#> >> 1 peaks(0.1536098%), having lengths smaller than 800bp, are filtered... 2023-07-02 17时03分17秒
#> >> Running bootstrapping for tag matrix...		 2023-07-02 17时03分54秒 
peak.anno <- AnnoPeak(
  peak.df = peak.df, species = "Mouse",
  seq.style = "UCSC", up.dist = 20000, down.dist = 20000
)
#> 
#> >> preparing features information...		 2023-07-02 17时03分56秒 
#> >> identifying nearest features...		 2023-07-02 17时03分56秒 
#> >> calculating distance from peak to TSS...	 2023-07-02 17时03分56秒 
#> >> assigning genomic annotation...		 2023-07-02 17时03分56秒 
#> >> adding gene annotation...			 2023-07-02 17时04分08秒 
#> 'select()' returned 1:many mapping between keys and columns
#> >> assigning chromosome lengths			 2023-07-02 17时04分08秒 
#> >> done...					 2023-07-02 17时04分08秒 
#> Warning: Removed 6 rows containing non-finite values (`stat_count()`).