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limma Result Categories

limma analysis results can be divided into three categories, which are defined in this document:

  1. Time Effect: This category focuses on the changes of the feature (e.g. protein) value that occur over time within a single condition.

  2. Average Difference Between Conditions: This category compares the average feature values for levels within a condition, regardless of time.

  3. Interaction Between Condition and Time: This category examines the interaction between time and condition. It identifies features whose value changes differently over time depending on the condition.


Legend:

  • A hit is a feature (e.g. a protein) that is significantly changed over time.
  • Levels are the different factors of a condition of the experiment. For example, bioreactor phase is a condition, and exponential and stationary are levels within that condition.

Category 1 (time effect)

Temporal pattern within level for a given feature → Hit

Example of a Hit

A hit is a feature that shows a clear temporal pattern over time.

Clear temporal pattern over time

Clear temporal pattern over time

Example of No Hit
No clear temporal pattern

No clear temporal pattern

Category 2 (average difference conditions)

Overall mean difference between levels for a given feature → Hit

Example of a Hit
No clear temporal pattern for both levels but overall mean difference between them

No clear temporal pattern for both levels but overall mean difference between them

Example of No Hit
Clear temporal pattern for both levels but no overall mean difference in feature value between them.

Clear temporal pattern for both levels but no overall mean difference in feature value between them.

Category 3 (interaction condition & time)

Treatment interacting with time for a feature (time effect changing with treatment, the feature must have different temporal patterns in both conditions/levels) → Hit

Examples of Hits

Different temporal patterns are observed for each level –> hit in category 3.

Different temporal patterns of the feature for both levels.

Different temporal patterns of the feature for both levels.

Different temporal patterns of the feature for both levels.

Different temporal patterns of the feature for both levels.

Example of No Hit
Overall the same temporal pattern of a feature for both levels.

Overall the same temporal pattern of a feature for both levels.

Session Info

## R version 4.3.3 (2024-02-29)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 22.04.5 LTS
## 
## Matrix products: default
## BLAS:   /usr/local/R-4.3.3/lib/R/lib/libRblas.so 
## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.10.0
## 
## locale:
##  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
##  [3] LC_TIME=de_AT.UTF-8        LC_COLLATE=en_US.UTF-8    
##  [5] LC_MONETARY=de_AT.UTF-8    LC_MESSAGES=en_US.UTF-8   
##  [7] LC_PAPER=de_AT.UTF-8       LC_NAME=C                 
##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
## [11] LC_MEASUREMENT=de_AT.UTF-8 LC_IDENTIFICATION=C       
## 
## time zone: Europe/Vienna
## tzcode source: system (glibc)
## 
## attached base packages:
## [1] stats     graphics  grDevices datasets  utils     methods   base     
## 
## loaded via a namespace (and not attached):
##  [1] digest_0.6.37       desc_1.4.3          R6_2.6.1           
##  [4] fastmap_1.2.0       xfun_0.50           cachem_1.1.0       
##  [7] knitr_1.49          htmltools_0.5.8.1   rmarkdown_2.29     
## [10] lifecycle_1.0.4     cli_3.6.4           sass_0.4.9         
## [13] pkgdown_2.1.1       textshaping_1.0.0   jquerylib_0.1.4    
## [16] renv_1.1.1          systemfonts_1.2.1   compiler_4.3.3     
## [19] rstudioapi_0.17.1   tools_4.3.3         ragg_1.3.3         
## [22] bslib_0.9.0         evaluate_1.0.3      yaml_2.3.10        
## [25] BiocManager_1.30.25 jsonlite_1.8.9      htmlwidgets_1.6.4  
## [28] rlang_1.1.5         fs_1.6.5