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Plot summary visualizations for the differential expression results

Source: R/diff_expression.R
plot_de_summary.Rd

plot_de_summary() creates summary visualizations for the differential expression results. It plots a barplot with the number of significant proteins for each disease. It also creates upset plots both for the significant up and down regulated proteins for each disease.

Usage

plot_de_summary(
  de_results,
  disease_palette = NULL,
  diff_exp_palette = "diff_exp",
  verbose = TRUE
)

Arguments

de_results

A list of differential expression results.

disease_palette

The color palette for the disease. If it is a character, it should be one of the palettes from get_hpa_palettes(). Default is NULL.

diff_exp_palette

The color palette for the differential expression. If it is a character, it should be one of the palettes from get_hpa_palettes(). Default is "diff_exp".

verbose

If the function should print the different sets of significant proteins for each disease. Default is TRUE.

Value

A list containing the following plots:

  • de_barplot: A barplot with the number of significant proteins for each disease.

  • upset_plot_up: An upset plot with the significant up regulated proteins for each disease.

  • upset_plot_down: An upset plot with the significant down regulated proteins for each disease.

  • proteins_df_up: A tibble with the significant up regulated proteins for each combination of diseases.

  • proteins_df_down: A tibble with the significant down regulated proteins for each combination of diseases.

  • proteins_list_up: A list with the significant up regulated proteins for each combination of diseases.

  • proteins_list_down: A list with the significant down regulated proteins for each combination of diseases.

Examples

# Run differential expression analysis for 3 different cases
de_results_aml <- do_limma(example_data,
                           example_metadata,
                           case = "AML",
                           control = c("BRC", "PRC"),
                           wide = FALSE,
                           only_female = "BRC",
                           only_male = "PRC")
#> Comparing AML with BRC, PRC.
#> Warning: 436 rows were removed because they contain NAs in Disease or Sex, Age!

de_results_brc <- do_limma(example_data,
                           example_metadata,
                           case = "BRC",
                           control = c("AML", "PRC"),
                           wide = FALSE,
                           only_female = "BRC",
                           only_male = "PRC")
#> Comparing BRC with AML, PRC.
#> Warning: 293 rows were removed because they contain NAs in Disease or Sex, Age!

de_results_prc <- do_limma(example_data,
                           example_metadata,
                           case = "PRC",
                           control = c("AML", "BRC"),
                           wide = FALSE,
                           only_female = "BRC",
                           only_male = "PRC")
#> Comparing PRC with AML, BRC.
#> Warning: 143 rows were removed because they contain NAs in Disease or Sex, Age!

# Combine the results
res <- list("AML" = de_results_aml,
            "BRC" = de_results_brc,
            "PRC" = de_results_prc)

# Plot summary visualizations
plot_de_summary(res)
#> [1] "AML" "PRC" "BRC"
#> # A tibble: 35 × 3
#>    `Shared in` `up/down` Assay   
#>    <chr>       <chr>     <chr>   
#>  1 AML         up        ABL1    
#>  2 PRC         up        ACAN    
#>  3 AML         up        ACE2    
#>  4 AML         up        ACTA2   
#>  5 AML         up        ADA     
#>  6 AML         up        ADA2    
#>  7 BRC         up        ADAMTS13
#>  8 BRC&PRC     up        ADAMTS8 
#>  9 AML         up        ADGRG1  
#> 10 BRC&PRC     up        ADGRG2  
#> # ℹ 25 more rows
#> # A tibble: 35 × 3
#>    `Shared in` `up/down` Assay   
#>    <chr>       <chr>     <chr>   
#>  1 BRC         up        ABL1    
#>  2 AML         up        ACAN    
#>  3 BRC         up        ACE2    
#>  4 BRC&PRC     up        ACTA2   
#>  5 BRC&PRC     up        ADA     
#>  6 BRC         up        ADA2    
#>  7 AML         up        ADAMTS13
#>  8 AML         up        ADAMTS8 
#>  9 BRC         up        ADGRE5  
#> 10 BRC&PRC     up        ADGRG1  
#> # ℹ 25 more rows
#> $de_barplot

#> 
#> $upset_plot_up

#> 
#> $upset_plot_down

#> 
#> $proteins_df_up
#> # A tibble: 35 × 3
#>    `Shared in` `up/down` Assay   
#>    <chr>       <chr>     <chr>   
#>  1 AML         up        ABL1    
#>  2 PRC         up        ACAN    
#>  3 AML         up        ACE2    
#>  4 AML         up        ACTA2   
#>  5 AML         up        ADA     
#>  6 AML         up        ADA2    
#>  7 BRC         up        ADAMTS13
#>  8 BRC&PRC     up        ADAMTS8 
#>  9 AML         up        ADGRG1  
#> 10 BRC&PRC     up        ADGRG2  
#> # ℹ 25 more rows
#> 
#> $proteins_df_down
#> # A tibble: 35 × 3
#>    `Shared in` `up/down` Assay   
#>    <chr>       <chr>     <chr>   
#>  1 BRC         up        ABL1    
#>  2 AML         up        ACAN    
#>  3 BRC         up        ACE2    
#>  4 BRC&PRC     up        ACTA2   
#>  5 BRC&PRC     up        ADA     
#>  6 BRC         up        ADA2    
#>  7 AML         up        ADAMTS13
#>  8 AML         up        ADAMTS8 
#>  9 BRC         up        ADGRE5  
#> 10 BRC&PRC     up        ADGRG1  
#> # ℹ 25 more rows
#> 
#> $proteins_list_up
#> $proteins_list_up$AML
#>  [1] "ADA"      "APEX1"    "AZU1"     "APBB1IP"  "ANGPT2"   "ARTN"    
#>  [7] "ADGRG1"   "ACTA2"    "AHCY"     "AGRP"     "ARID4B"   "B4GALT1" 
#> [13] "ABL1"     "ADM"      "ATP6V1F"  "ATP6AP2"  "ANGPTL4"  "AMFR"    
#> [19] "AREG"     "ACE2"     "ATF2"     "ADA2"     "AIF1"     "ARHGAP25"
#> 
#> $proteins_list_up$`BRC&PRC`
#> [1] "ANGPT1"  "ADGRG2"  "ADAMTS8"
#> 
#> $proteins_list_up$BRC
#> [1] "ANGPT1"   "ADGRG2"   "ADAMTS8"  "ADAMTS13" "ART3"    
#> 
#> $proteins_list_up$PRC
#> [1] "ATG4A"   "ADAMTS8" "ANGPT1"  "APOM"    "ADGRG2"  "ALDH1A1" "AMY2B"  
#> [8] "ALPP"    "ACAN"   
#> 
#> 
#> $proteins_list_down
#> $proteins_list_down$AML
#>  [1] "ANGPT1"   "ADAMTS8"  "ADGRG2"   "APOM"     "ATG4A"    "ADAMTS13"
#>  [7] "ARHGEF12" "APP"      "ALPP"     "ACAN"     "ANGPTL7" 
#> 
#> $proteins_list_down$`BRC&PRC`
#>  [1] "ADA"     "AZU1"    "APEX1"   "APBB1IP" "ARTN"    "ANGPT2"  "ACTA2"  
#>  [8] "AGRP"    "ARID4B"  "ADGRG1" 
#> 
#> $proteins_list_down$BRC
#>  [1] "ADA"      "AZU1"     "APEX1"    "APBB1IP"  "AHCY"     "ARTN"    
#>  [7] "ANGPT2"   "ACTA2"    "B4GALT1"  "ABL1"     "AGRP"     "ARID4B"  
#> [13] "ACE2"     "ADA2"     "ADGRG1"   "ARHGAP25" "ATF2"     "ARSA"    
#> [19] "ADGRE5"  
#> 
#> $proteins_list_down$PRC
#>  [1] "ADGRG1"  "APEX1"   "ADA"     "AZU1"    "ARTN"    "ANGPT2"  "ATP6AP2"
#>  [8] "AGRP"    "APBB1IP" "ADM"     "AREG"    "ARID4B"  "ATP6V1F" "ANGPTL4"
#> [15] "ACTA2"  
#> 
#>