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Aggregation plot

Source: R/ggAPA.R
ggAPA.Rd

Create a ggplot object used for plot aggregation.

Usage

ggAPA(
  aggregatedMtx = NULL,
  title = NULL,
  trim = 0,
  tails = "both",
  colMin = NULL,
  colMid = NULL,
  colMax = NULL,
  colBreaks = NULL,
  blurPass = 0,
  boxKernel = NULL,
  kernSize = NULL,
  stdev = 0.5,
  loTri = NULL,
  colors = NULL,
  na.value = "#F2F2F2",
  colorScale = "linear",
  bias = 1,
  paletteLength = 51,
  annotate = TRUE,
  anchor.name = "Anchor",
  bait.name = "Bait",
  fixCoord = TRUE,
  triangular = FALSE
)

Arguments

aggregatedMtx

: The matrix to plot. (Default NULL)

title

: The title of plot. (Default NULL)

trim

: A number between 0 and 100 that gives the percentage of trimming. (Default 0)

tails

: Which boundary must be trimmed? If it's both, trim half of the percentage in inferior and superior. see QtlThreshold. (Default "both")

colMin

: Minimal value of Heatmap, force color range. If NULL automatically find. (Default NULL)

colMid

: Center value of Heatmap, force color range. If NULL automatically find. (Default NULL)

colMax

: Maximal value of Heatmap, force color range. If NULL automatically find. (Default NULL)

colBreaks

: Repartition of colors. If NULL automatically find. (Default NULL)

blurPass

: Number of blur pass. (Default 0)

boxKernel

: If NULL automatically compute for 3 Sd. (Default NULL)

kernSize

: Size of box applied to blurr. If NULL automatically compute for 3 Sd. (Default NULL)

stdev

: SD of gaussian smooth. (Default 0.5)

loTri

: The value that replace all value in the lower triangle of matrice (Usefull when blur is apply).(Default NULL)

colors

: Heatmap color list. If NULL, automatically compute. (Default NULL)

na.value

: Color of NA values. (Default "#F2F2F2")

colorScale

: Shape of color scale on of "linear" or "density" based. (Default "linear")

bias

: A positive number. Higher values give more widely spaced colors at the high end. See ?grDevices::colorRamp for more details. (Default 1)

paletteLength

: The number of color in the palette. (Default 51)

annotate

: Should there be axis ticks? (Default: TRUE)

anchor.name

Name of anchor for annotation. (Default "Anchor")

bait.name

Name of bait for annotation. (Default "Bait")

fixCoord

Fix axes coordinates? (Default TRUE)

triangular

plot in a triangular format? available when matrices are extracted in "rf" mode only. (Default FALSE) (Default TRUE)

Value

A ggplot object.

Details

ggAPA

Examples

# Data
data(Beaf32_Peaks.gnr)
data(HiC_Ctrl.cmx_lst)

# Index Beaf32
Beaf32_Index.gnr <- IndexFeatures(
    gRangeList = list(Beaf = Beaf32_Peaks.gnr),
    chromSizes = data.frame(seqnames = c("2L", "2R"),
        seqlengths = c(23513712, 25286936)),
    binSize = 100000
)

# Beaf32 <-> Beaf32 Pairing
Beaf_Beaf.gni <- SearchPairs(indexAnchor = Beaf32_Index.gnr)
Beaf_Beaf.gni <- Beaf_Beaf.gni[seq_len(2000)] 
# subset 2000 first for exemple

# Matrices extractions center on Beaf32 <-> Beaf32 point interaction
interactions_PF.mtx_lst <- ExtractSubmatrix(
    genomicFeature = Beaf_Beaf.gni,
    hicLst = HiC_Ctrl.cmx_lst,
    referencePoint = "pf"
)

# Aggregate matrices in one matrix
aggreg.mtx <- Aggregation(interactions_PF.mtx_lst)

# Visualization
ggAPA(
    aggregatedMtx = aggreg.mtx
)


# Add Title
ggAPA(
    aggregatedMtx = aggreg.mtx,
    title = "APA"
)


# Trim values
ggAPA(
    aggregatedMtx = aggreg.mtx,
    title = "APA 30% trimmed on upper tail of distribution",
    trim = 30,
    tails = "upper"
)
#> Warning: no non-missing arguments to max; returning -Inf

ggAPA(
    aggregatedMtx = aggreg.mtx,
    title = "APA 30% trimmed on lower tail of distribution",
    trim = 30,
    tails = "lower"
)
#> Warning: no non-missing arguments to min; returning Inf

ggAPA(
    aggregatedMtx = aggreg.mtx,
    title = "APA 15% trimmed on each tail of distribution",
    trim = 30,
    tails = "both"
)


# Change Minimal, Central and Maximal Colors scale value
ggAPA(
    aggregatedMtx = aggreg.mtx,
    title = "APA [min 200, center 300, max 600]",
    colMin = 200,
    colMid = 300,
    colMax = 600
)


# Change Color
ggAPA(
    aggregatedMtx = aggreg.mtx,
    title = "APA",
    colors = viridis(6),
    na.value = "black"
)

ggAPA(
    aggregatedMtx = aggreg.mtx,
    title = "APA",
    colors = c("black", "white"),
)


# Change Color distribution
ggAPA(
    aggregatedMtx = aggreg.mtx,
    title = "APA [100,150,200,250,300,350,600]",
    colBreaks = c(100, 150, 200, 250, 300, 350, 600) # Choosen Breaks
)

ggAPA(
    aggregatedMtx = aggreg.mtx,
    title = "APA",
    colorScale = "density" # color distribution based on density
)

ggAPA(
    aggregatedMtx = aggreg.mtx,
    title = "APA",
    bias = 2 # (>1 wait on extremums)
)

ggAPA(
    aggregatedMtx = aggreg.mtx,
    title = "APA",
    bias = 0.5 # (<1 wait on center)
)


# Apply a Blurr
ggAPA(
    aggregatedMtx = aggreg.mtx,
    title = "APA",
    blurPass = 1,
    stdev = 0.5
)


# ggplot2 object modifications
# Since the function returns a ggplot object, it is possible
# to modify it following the ggplot2 grammar.
ggAPA(
    aggregatedMtx = aggreg.mtx,
    title = "APA",
) +
    ggplot2::labs(
        title = "New title",
        subtitle = "and subtitle"
    )