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Plot features summary visualizations

Source: R/classification_models.R
plot_features_summary.Rd

plot_features_summary() plots the number of proteins and the number of top proteins for each disease in a barplot. It also plots the upset plot of the top or all protein features, as well as a summary line plot of the model performance metrics.

Usage

plot_features_summary(
  ml_results,
  importance = 50,
  upset_top_features = FALSE,
  case_palette = NULL,
  feature_type_palette = c(`all-features` = "pink", `top-features` = "darkblue"),
  verbose = TRUE
)

Arguments

ml_results

A list of classification models results.

importance

Importance threshold for top features. Default is 50.

upset_top_features

Whether to plot the upset plot for the top features. Default is FALSE.

case_palette

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

feature_type_palette

The color palette for the plot. If it is a character, it should be one of the palettes from get_hpa_palettes(). Default is "all-features" = "pink" and "top-features" = "darkblue".

verbose

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

Value

A list with two elements:

  • features_barplot: Barplot of the number of proteins and top proteins for each disease.

  • upset_plot_features: Upset plot of the top or all proteins.

  • metrics_barplot: Barplot of the model metrics for each disease.

  • features_df: A tibble with the proteins for each combination of cases.

  • features_list: A list with the proteins for each combination of cases.

Examples

# Run the elastic net model pipeline for 3 different cases
res_aml <- do_rreg(example_data,
                   example_metadata,
                   case = "AML",
                   control = c("BRC", "PRC"),
                   wide = FALSE,
                   only_female = "BRC",
                   only_male = "PRC",
                   cv_sets = 2,
                   grid_size = 1,
                   ncores = 1)
#> Joining with `by = join_by(DAid)`
#> Sets and groups are ready. Model fitting is starting...
#> Classification model for AML as case is starting...
#> Warning: Due to the small size of the grid, a Latin hypercube design will be used.

res_brc <- do_rreg(example_data,
                   example_metadata,
                   case = "BRC",
                   control = c("BRC", "AML"),
                   wide = FALSE,
                   only_female = "BRC",
                   only_male = "PRC",
                   cv_sets = 2,
                   grid_size = 1,
                   ncores = 1)
#> Joining with `by = join_by(DAid)`
#> Sets and groups are ready. Model fitting is starting...
#> Classification model for BRC as case is starting...
#> Warning: Due to the small size of the grid, a Latin hypercube design will be used.

res_prc <- do_rreg(example_data,
                   example_metadata,
                   case = "PRC",
                   control = c("BRC", "AML"),
                   wide = FALSE,
                   only_female = "BRC",
                   only_male = "PRC",
                   cv_sets = 2,
                   grid_size = 1,
                   ncores = 1)
#> Joining with `by = join_by(DAid)`
#> Sets and groups are ready. Model fitting is starting...
#> Classification model for PRC as case is starting...
#> Warning: Due to the small size of the grid, a Latin hypercube design will be used.

# Combine the results
res <- list("AML" = res_aml,
            "BRC" = res_brc,
            "PRC" = res_prc)

# Plot features summary visualizations
plot_features_summary(res)
#> $`AML&PRC`
#>  [1] "ADGRG1"  "APEX1"   "ALDH1A1" "ADM"     "ADA"     "ANGPT1"  "AHSP"   
#>  [8] "ALPP"    "ACP6"    "ADGRE2"  "ATP6AP2" "AIF1"   
#> 
#> $`AML&BRC`
#> [1] "ADGRG2"  "ADA"     "ANGPT1"  "ACTA2"   "B4GALT1"
#> 
#> $AML
#>  [1] ADGRG1  APEX1   ADGRG2  ALDH1A1 ADM     ANXA11  ADA     ANGPT1  AHCY   
#> [10] AGR3    ARNT    ARID4B  AHSP    AGER    ACTA2   ADAMTS8 ALPP    ACP6   
#> [19] AGR2    ANXA5   AOC1    ADGRE2  ATF2    ANGPTL1 ABL1    B4GALT1 APBB1IP
#> [28] ATP6AP2 AIF1    ALDH3A1
#> 100 Levels: AARSD1 ACAA1 ACAN ACE2 ACOX1 ACP5 ACTN4 ACY1 ADA2 ADAM15 ... ADGRG1
#> 
#> $`AML&BRC&PRC`
#> [1] "ADA"    "ANGPT1"
#> 
#> $BRC
#>  [1] ADA      ANGPT1   ADGRG2   ANGPTL2  ADAMTS13 ACTA2    AMIGO2   B4GALT1 
#>  [9] ANGPT2   ADAMTS15 ATP6V1D  ACTN4   
#> 100 Levels: AARSD1 ABL1 ACAA1 ACAN ACE2 ACOX1 ACP5 ACP6 ACY1 ADA2 ... ADA
#> 
#> $`BRC&PRC`
#> [1] "ADA"    "ANGPT1" "AMIGO2" "ANGPT2"
#> 
#> $PRC
#>  [1] APEX1   ALPP    ADM     ANGPT1  ALDH1A1 ACP6    ATP6AP2 AMBN    ADA    
#> [10] AMIGO2  ACAN    ANGPTL4 ADGRE5  AIF1    APOM    ANGPT2  ADGRG1  ADGRE2 
#> [19] ATOX1   ADH4    ANGPTL7 AZU1    APLP1   AHSP    ATP5PO  ALCAM  
#> 100 Levels: AARSD1 ABL1 ACAA1 ACE2 ACOX1 ACP5 ACTA2 ACTN4 ACY1 ADA2 ... APEX1
#> 
#> $features_barplot

#> 
#> $upset_plot_features

#> 
#> $metrics_lineplot

#> 
#> $features_df
#> # A tibble: 49 × 3
#>    `Shared in` `up/down` Assay   
#>    <chr>       <chr>     <chr>   
#>  1 AML         up        ABL1    
#>  2 PRC         up        ACAN    
#>  3 AML&PRC     up        ACP6    
#>  4 AML&BRC     up        ACTA2   
#>  5 BRC         up        ACTN4   
#>  6 AML&BRC&PRC up        ADA     
#>  7 BRC         up        ADAMTS13
#>  8 BRC         up        ADAMTS15
#>  9 AML         up        ADAMTS8 
#> 10 AML&PRC     up        ADGRE2  
#> # ℹ 39 more rows
#> 
#> $features_list
#> $features_list$`AML&PRC`
#>  [1] "ADGRG1"  "APEX1"   "ALDH1A1" "ADM"     "ADA"     "ANGPT1"  "AHSP"   
#>  [8] "ALPP"    "ACP6"    "ADGRE2"  "ATP6AP2" "AIF1"   
#> 
#> $features_list$`AML&BRC`
#> [1] "ADGRG2"  "ADA"     "ANGPT1"  "ACTA2"   "B4GALT1"
#> 
#> $features_list$AML
#>  [1] ADGRG1  APEX1   ADGRG2  ALDH1A1 ADM     ANXA11  ADA     ANGPT1  AHCY   
#> [10] AGR3    ARNT    ARID4B  AHSP    AGER    ACTA2   ADAMTS8 ALPP    ACP6   
#> [19] AGR2    ANXA5   AOC1    ADGRE2  ATF2    ANGPTL1 ABL1    B4GALT1 APBB1IP
#> [28] ATP6AP2 AIF1    ALDH3A1
#> 100 Levels: AARSD1 ACAA1 ACAN ACE2 ACOX1 ACP5 ACTN4 ACY1 ADA2 ADAM15 ... ADGRG1
#> 
#> $features_list$`AML&BRC&PRC`
#> [1] "ADA"    "ANGPT1"
#> 
#> $features_list$BRC
#>  [1] ADA      ANGPT1   ADGRG2   ANGPTL2  ADAMTS13 ACTA2    AMIGO2   B4GALT1 
#>  [9] ANGPT2   ADAMTS15 ATP6V1D  ACTN4   
#> 100 Levels: AARSD1 ABL1 ACAA1 ACAN ACE2 ACOX1 ACP5 ACP6 ACY1 ADA2 ... ADA
#> 
#> $features_list$`BRC&PRC`
#> [1] "ADA"    "ANGPT1" "AMIGO2" "ANGPT2"
#> 
#> $features_list$PRC
#>  [1] APEX1   ALPP    ADM     ANGPT1  ALDH1A1 ACP6    ATP6AP2 AMBN    ADA    
#> [10] AMIGO2  ACAN    ANGPTL4 ADGRE5  AIF1    APOM    ANGPT2  ADGRG1  ADGRE2 
#> [19] ATOX1   ADH4    ANGPTL7 AZU1    APLP1   AHSP    ATP5PO  ALCAM  
#> 100 Levels: AARSD1 ABL1 ACAA1 ACE2 ACOX1 ACP5 ACTA2 ACTN4 ACY1 ADA2 ... APEX1
#> 
#>