Heatmap group for visualizing grouped gene expression data.

Usage

heatmap_group(
  sample_gene,
  group_sample,
  scale_data = "row",
  clust_method = "complete",
  border_show = TRUE,
  border_color = "#ffffff",
  value_show = TRUE,
  value_decimal = 2,
  value_size = 5,
  axis_size = 8,
  cell_height = 10,
  low_color = "#00880055",
  mid_color = "#ffffff",
  high_color = "#ff000055",
  na_color = "#ff8800",
  x_angle = 45
)

Arguments

sample_gene: Dataframe: Shared degs of all paired comparisons in all samples expression dataframe of RNA-Seq. (1st-col: Genes, 2nd-col~: Samples).
group_sample: Dataframe: Samples and groups for gene expression (1st-col: Samples, 2nd-col: Groups).
scale_data: Character: scale data. Default: "row", options: "row", "column", "none".
clust_method: Character: cluster method. Default: "complete", options: "ward.D", "ward.D2", "single", "complete", "average" (= UPGMA), "mcquitty" (= WPGMA), "median" (= WPGMC) or "centroid" (= UPGMC).
border_show: Logical: show border. Default: TRUE, options: TRUE, FALSE.
border_color: Character: cell border color (color value or hex value with alpha). Default: "#ffffff".
value_show: Logical: show value in cell. Default: TRUE, options: TRUE, FALSE.
value_decimal: Numeric: cell value decimal. Default: 2, min: 0, max: 5.
value_size: Numeric: cell value font size. Default: 5, min: 0, max: NULL.
axis_size: Numeric: axis title font size. Default: 8, min: 0, max: NULL.
cell_height: Numeric: cell height for value size and axis size. Default: 10.
low_color: Character: min value color (color value or hex value with alpha). Default: "#00880055".
mid_color: Character: min value color (color value or hex value with alpha). Default: "#ffffff".
high_color: Character: min value color (color value or hex value with alpha). Default: "#ff000055".
na_color: Character: min value color (color value or hex value with alpha). Default: "#ff8800".
x_angle: Numeric: x axis text angle. Default: 45, min: 0, max: 360.

Value

Plot: Heatmap group for visualizing grouped gene expression data.

Author

benben-miao

Examples

# 1. Library TOmicsVis package
library(TOmicsVis)

# 2. Use example dataset
data(gene_expression2)
head(gene_expression2)
#>   Genes  CT_1    CT_2  CT_3 LT20_1 LT20_2 LT20_3 LT15_1 LT15_2 LT15_3 LT12_1
#> 1 ACAA2 24.50   39.83 55.38 114.11 159.32  96.88 169.56 464.84 182.66 116.08
#> 2  ACAN 14.97   18.71 10.30  71.23 142.67 213.54 253.15 320.80 104.15 174.02
#> 3  ADH1  1.54    1.56  2.04  14.95  13.60  15.87  12.80  17.74   6.06  10.97
#> 4  AHSG  0.00 1911.99  0.00   0.00   0.00   0.00   0.00   0.00   0.00   0.00
#> 5 ALDH2  2.07    2.86  2.54   0.85   0.49   0.47   0.42   0.13   0.26   0.00
#> 6 AP1S3  6.62   14.59  9.30  24.90  33.94  23.19  24.00  36.08  27.40  24.06
#>   LT12_2 LT12_3 LT12_6_1 LT12_6_2 LT12_6_3
#> 1 497.29 464.48   471.43   693.62   229.77
#> 2 305.81 469.48  1291.90   991.90   966.77
#> 3  10.71  30.95     9.84    10.91     7.28
#> 4   0.00   0.00     0.00     0.00     0.00
#> 5   0.28   0.11     0.37     0.15     0.11
#> 6  38.74  34.54    62.72    41.36    28.75

data(samples_groups)
head(samples_groups)
#>   Samples Groups
#> 1    CT_1     CT
#> 2    CT_2     CT
#> 3    CT_3     CT
#> 4  LT20_1   LT20
#> 5  LT20_2   LT20
#> 6  LT20_3   LT20

# 3. Default parameters
heatmap_group(gene_expression2[1:50,], samples_groups)


# 4. Set scale_data = "column"
heatmap_group(gene_expression2[1:50,], samples_groups, scale_data = "column")


# 5. Set value_show = FALSE
heatmap_group(gene_expression2[1:50,], samples_groups, value_show = FALSE)


# 6. Set low_color = "#00008888"
heatmap_group(gene_expression2[1:50,], samples_groups, low_color = "#00008888")