GO Enrichment on Two Peak Annotation/Differential Analysis Integration Results.

PeakbPeakFE(
  peak.peak,
  peak.fe.key,
  out.folder = NULL,
  gene.type = c("ENSEMBL", "ENTREZID", "SYMBOL"),
  go.type = c("ALL", "BP", "MF", "CC"),
  enrich.pvalue = 0.05,
  enrich.qvalue = 0.05,
  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"),
  padj.method = c("BH", "holm", "hochberg", "hommel", "bonferroni", "BY", "fdr",
    "none"),
  show.term = 15,
  str.width = 30,
  plot.resolution = 300,
  plot.width = 7,
  plot.height = 9,
  save = TRUE
)

Arguments

peak.peak	Dataframe contains integrated results of two peak annotation/differential analysis.
peak.fe.key	The key type of integrated results ("Type" column of `peak.peak`) to perform functional enrichment.
out.folder	Folder to save enrichment results. Default: wording directory.
gene.type	Gene name type of `P1_Gene` column. Chosen from ENSEMBL, ENTREZID,SYMBOL. Default: ENSEMBL.
go.type	GO enrichment type, chosen from ALL, BP, MF, CC. Default: ALL.
enrich.pvalue	Cutoff value of pvalue. Default: 0.05.
enrich.qvalue	Cutoff value of qvalue. Default: 0.05.
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".
padj.method	One of "holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none". Default: BH.
show.term	Number of enrichment term to show. Default: 15.
str.width	Length of enrichment term in plot. Default: 30.
plot.resolution	Resolution of plot. Default: 300.
plot.width	The width of plot. Default: 7.
plot.height	The height of plot. Default: 9.
save	Logical value, whether to save all results. Default: TRUE.

Value

If save is TRUE, return NULL (all results are in out.folder), else retutn result dataframe.

Examples

library(DEbPeak)
# ChIP-seq data
chip.file <- system.file("extdata", "debchip_peaks.bed", package = "DEbPeak")
chip.df <- GetConsensusPeak(peak.file = chip.file)
chip.anno <- AnnoPeak(
  peak.df = chip.df, species = "Mouse",
  seq.style = "UCSC", up.dist = 20000, down.dist = 20000
)
#> >> preparing features information...		 2023-07-02 17时22分56秒 
#> >> identifying nearest features...		 2023-07-02 17时22分56秒 
#> >> calculating distance from peak to TSS...	 2023-07-02 17时22分57秒 
#> >> assigning genomic annotation...		 2023-07-02 17时22分57秒 
#> >> adding gene annotation...			 2023-07-02 17时22分58秒 
#> 'select()' returned 1:many mapping between keys and columns
#> >> assigning chromosome lengths			 2023-07-02 17时22分59秒 
#> >> done...					 2023-07-02 17时22分59秒 
#> Warning: Removed 6 rows containing non-finite values (`stat_count()`).
# ATAC-seq data
atac.file <- system.file("extdata", "debatac_peaks.bed", package = "DEbPeak")
atac.df <- GetConsensusPeak(peak.file = atac.file)
atac.anno <- AnnoPeak(
  peak.df = atac.df, species = "Mouse",
  seq.style = "UCSC", up.dist = 20000, down.dist = 20000
)
#> >> preparing features information...		 2023-07-02 17时23分00秒 
#> >> identifying nearest features...		 2023-07-02 17时23分00秒 
#> >> calculating distance from peak to TSS...	 2023-07-02 17时23分00秒 
#> >> assigning genomic annotation...		 2023-07-02 17时23分00秒 
#> >> adding gene annotation...			 2023-07-02 17时23分02秒 
#> 'select()' returned 1:many mapping between keys and columns
#> >> assigning chromosome lengths			 2023-07-02 17时23分02秒 
#> >> done...					 2023-07-02 17时23分02秒 
#> Warning: Removed 23 rows containing non-finite values (`stat_count()`).
# integrate
chip.atac <- PeakbPeak(peak1.res = chip.anno$df, peak2.res = atac.anno$df, peak.mode = "consensus", peak.anno.key = "Promoter")
# functional enrichment
chip.atac.fe <- PeakbPeakFE(
  peak.peak = chip.atac, peak.fe.key = "Common", gene.type = "SYMBOL",
  go.type = "BP", species = "Mouse", save = FALSE
)
#> Convert SYMBOL to ENTREZID!
#> 'select()' returned 1:1 mapping between keys and columns
#> Warning: 0.61% of input gene IDs are fail to map...
#> conduct BP GO enrichment analysis.
#> wrong orderBy parameter; set to default `orderBy = "x"`
#> Scale for y is already present.
#> Adding another scale for y, which will replace the existing scale.