Data preparation

library(massdataset)
library(tidyverse)
library(demodata)
library(massstat)

data("liver_aging_pos", package = "demodata")
liver_aging_pos
#> -------------------- 
#> massdataset version: 0.01 
#> -------------------- 
#> 1.expression_data:[ 21607 x 24 data.frame]
#> 2.sample_info:[ 24 x 4 data.frame]
#> 3.variable_info:[ 21607 x 3 data.frame]
#> 4.sample_info_note:[ 4 x 2 data.frame]
#> 5.variable_info_note:[ 3 x 2 data.frame]
#> 6.ms2_data:[ 0 variables x 0 MS2 spectra]
#> -------------------- 
#> Processing information (extract_process_info())
#> Creation ---------- 
#>       Package         Function.used                Time
#> 1 massdataset create_mass_dataset() 2021-12-23 00:24:02

w_78 =
  liver_aging_pos %>%
  activate_mass_dataset(what = "sample_info") %>%
  dplyr::filter(group == "78W") %>%
  dplyr::pull(sample_id)

w_24 =
  liver_aging_pos %>%
  activate_mass_dataset(what = "sample_info") %>%
  dplyr::filter(group == "24W") %>%
  dplyr::pull(sample_id)

control_sample_id = w_24
case_sample_id = w_78

liver_aging_pos =
  mutate_fc(
    object = liver_aging_pos,
    control_sample_id = control_sample_id,
    case_sample_id = case_sample_id,
    mean_median = "mean"
  )
#> 10 control samples.
#> 10 case samples.
#> 

liver_aging_pos =
  mutate_p_value(
    object = liver_aging_pos,
    control_sample_id = control_sample_id,
    case_sample_id = case_sample_id,
    method = "t.test",
    p_adjust_methods = "BH"
  )
#> 10 control samples.
#> 10 case samples.
#> 

object = liver_aging_pos

Volcano plot

volcano_plot(
  object = object,
  fc_column_name = "fc",
  p_value_column_name = "p_value_adjust",
  labs_x = "log2(Fold change)",
  labs_y = "-log(p-adjust, 10)",
  fc_up_cutoff = 2,
  fc_down_cutoff = 0.5,
  p_value_cutoff = 0.05,
  add_text = TRUE
)



volcano_plot(
  object = object,
  fc_column_name = "fc",
  p_value_column_name = "p_value",
  labs_x = "log2(Fold change)",
  labs_y = "-log(p-value, 10)",
  fc_up_cutoff = 2,
  fc_down_cutoff = 0.5,
  p_value_cutoff = 0.05,
  add_text = FALSE,
  point_alpha = 0.5
)


volcano_plot(
  object = object,
  fc_column_name = "fc",
  p_value_column_name = "p_value",
  labs_x = "log2(Fold change)",
  labs_y = "-log(p-value, 10)",
  fc_up_cutoff = 2,
  fc_down_cutoff = 0.5,
  p_value_cutoff = 0.05,
  add_text = FALSE,
  point_alpha = 0.5,
  point_size_scale = "p_value"
) +
  scale_size_continuous(range = c(0.5, 3))

Session information

sessionInfo()
#> R version 4.1.0 (2021-05-18)
#> Platform: x86_64-apple-darwin17.0 (64-bit)
#> Running under: macOS Big Sur 10.16
#> 
#> Matrix products: default
#> BLAS:   /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRblas.dylib
#> LAPACK: /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRlapack.dylib
#> 
#> locale:
#> [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
#> 
#> attached base packages:
#> [1] stats     graphics  grDevices utils     datasets  methods   base     
#> 
#> other attached packages:
#>  [1] ggfortify_0.4.12   massstat_0.99.1    demodata_0.0.1     forcats_0.5.1     
#>  [5] stringr_1.4.0      dplyr_1.0.7        purrr_0.3.4        readr_2.0.0       
#>  [9] tidyr_1.1.3        tibble_3.1.3       ggplot2_3.3.5      tidyverse_1.3.1   
#> [13] magrittr_2.0.1     tinytools_0.9.1    massdataset_0.99.1
#> 
#> loaded via a namespace (and not attached):
#>   [1] colorspace_2.0-2     rjson_0.2.20         ellipsis_0.3.2      
#>   [4] leaflet_2.0.4.1      rprojroot_2.0.2      circlize_0.4.14     
#>   [7] GlobalOptions_0.1.2  fs_1.5.0             clue_0.3-59         
#>  [10] rstudioapi_0.13      ggrepel_0.9.1        fansi_0.5.0         
#>  [13] lubridate_1.7.10     xml2_1.3.2           codetools_0.2-18    
#>  [16] doParallel_1.0.16    cachem_1.0.5         knitr_1.33          
#>  [19] jsonlite_1.7.2       Cairo_1.5-12.2       broom_0.7.9         
#>  [22] cluster_2.1.2        dbplyr_2.1.1         png_0.1-7           
#>  [25] BiocManager_1.30.16  compiler_4.1.0       httr_1.4.2          
#>  [28] rvcheck_0.1.8        backports_1.2.1      assertthat_0.2.1    
#>  [31] fastmap_1.1.0        lazyeval_0.2.2       cli_3.0.1           
#>  [34] htmltools_0.5.2      tools_4.1.0          gtable_0.3.0        
#>  [37] glue_1.4.2           Rcpp_1.0.7           Biobase_2.52.0      
#>  [40] cellranger_1.1.0     jquerylib_0.1.4      pkgdown_2.0.1       
#>  [43] vctrs_0.3.8          iterators_1.0.13     crosstalk_1.1.1     
#>  [46] xfun_0.24            openxlsx_4.2.4       rvest_1.0.1         
#>  [49] lifecycle_1.0.0      scales_1.1.1         ragg_1.1.3          
#>  [52] clisymbols_1.2.0     hms_1.1.0            parallel_4.1.0      
#>  [55] RColorBrewer_1.1-2   ComplexHeatmap_2.8.0 yaml_2.2.1          
#>  [58] memoise_2.0.0        pbapply_1.4-3        gridExtra_2.3       
#>  [61] sass_0.4.0           stringi_1.7.3        S4Vectors_0.30.0    
#>  [64] desc_1.3.0           foreach_1.5.1        BiocGenerics_0.38.0 
#>  [67] zip_2.2.0            BiocParallel_1.26.1  shape_1.4.6         
#>  [70] rlang_0.4.11         pkgconfig_2.0.3      systemfonts_1.0.2   
#>  [73] matrixStats_0.60.0   evaluate_0.14        patchwork_1.1.1     
#>  [76] htmlwidgets_1.5.3    tidyselect_1.1.1     ggsci_2.9           
#>  [79] plyr_1.8.6           R6_2.5.0             IRanges_2.26.0      
#>  [82] snow_0.4-3           generics_0.1.0       DBI_1.1.1           
#>  [85] pillar_1.6.2         haven_2.4.1          withr_2.4.2         
#>  [88] modelr_0.1.8         crayon_1.4.1         utf8_1.2.2          
#>  [91] plotly_4.9.4.1       tzdb_0.1.2           rmarkdown_2.9       
#>  [94] GetoptLong_1.0.5     grid_4.1.0           readxl_1.3.1        
#>  [97] data.table_1.14.0    reprex_2.0.0         digest_0.6.27       
#> [100] gridGraphics_0.5-1   textshaping_0.3.6    stats4_4.1.0        
#> [103] munsell_0.5.0        viridisLite_0.4.0    ggplotify_0.0.8     
#> [106] bslib_0.3.1