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I have the following data frame:


library(tidyverse)
dat <- structure(list(motif_and_gene_name = c("FCCT", "XXX4", "XXX2", 
"FCCT", "XXX4", "XXX2", "FCCT", "XXX4", "XXX2", "FCCT", "XXX4", 
"XXX2", "FCCT", "XXX4", "XXX2", "FCCT", "XXX4", "XXX2"), 
    tissue = c("DA", "DA", "DA", "MB", 
    "MB", "MB", "VL", "VL", "VL", "UP", 
    "UP", "UP", "BU", "BU", "BU", 
    "TV", "TV", "TV"), motif_enrichment = c(4740, 
    964.2, 539.2, 6634, 1860, 1150, 6312, 2146, 1432, 5336, 2282, 
    1381, 2796, 1947, 1175, 8190, 1576, 926.8), expression_tpm = c(5.095, 
    15.1825, 1.4225, 7.27, 23.7125, 6.85, 4.8775, 27.17, 3.0025, 
    6.0025, 23.3725, 5.1425, 5.4525, 20.215, 4.695, 6.44, 22.04, 
    4.24)), class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA, 
-18L), .Names = c("motif_and_gene_name", "tissue", "motif_enrichment", 
"expression_tpm"))

dat
#> # A tibble: 18 x 4
#>    motif_and_gene_name tissue motif_enrichment expression_tpm
#>                  <chr>  <chr>            <dbl>          <dbl>
#>  1                FCCT     DA           4740.0         5.0950
#>  2                XXX4     DA            964.2        15.1825
#>  3                XXX2     DA            539.2         1.4225
#>  4                FCCT     MB           6634.0         7.2700
#>  5                XXX4     MB           1860.0        23.7125
#>  6                XXX2     MB           1150.0         6.8500
#>  7                FCCT     VL           6312.0         4.8775
#>  8                XXX4     VL           2146.0        27.1700
#>  9                XXX2     VL           1432.0         3.0025
#> 10                FCCT     UP           5336.0         6.0025
#> 11                XXX4     UP           2282.0        23.3725
#> 12                XXX2     UP           1381.0         5.1425
#> 13                FCCT     BU           2796.0         5.4525
#> 14                XXX4     BU           1947.0        20.2150
#> 15                XXX2     BU           1175.0         4.6950
#> 16                FCCT     TV           8190.0         6.4400
#> 17                XXX4     TV           1576.0        22.0400
#> 18                XXX2     TV            926.8         4.2400

With the following code 

mycol <- c("#3D1E1F","#FE677E","#F19068","#E8A99D","#FCDED4")
nof_vals <- length(dat$expression_tpm)

dat %>% 
  ggplot(aes(x=tissue,y=motif_and_gene_name, size=motif_enrichment, colour=factor(expression_tpm))) + 
  geom_point(stat = "identity")  + 
  scale_colour_manual(values =  colorRampPalette(mycol)(nof_vals)) +
  theme_minimal()

I can create this:

enter image description here

The size of circle is determined by motif enrichment and the color range is by expression tpm. Notice now there are 4 size of circles and 18 colours. How can I fix the scale to N=5 for both size and colours with a predifined breaks like:

size range:  motif_enrichment <=100 101-500 501-1000 1001-1500 >1500
color range: expression_tpm   <=1   2-5     6-10     11-15   >15
littleworth
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1 Answers1

2

You have to make a variable where you define breaks. Use cut.

dat$expr_brks <- cut(dat$expression_tpm, breaks = c(-Inf, 1, 5, 10, 16, 20, Inf))
dat$motif_brks <- cut(dat$motif_enrichment, breaks = c(-Inf, 100, 500, 1000, 1500, 2000, Inf))

dat %>% 
  ggplot(aes(x = tissue,y = motif_and_gene_name, size = motif_brks, color = expr_brks)) + 
  geom_point(stat = "identity")  + 
  scale_color_manual(values = colorRampPalette(mycol)(length(levels(dat$expr_brks)))) +
  theme_minimal()
Roman Luštrik
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