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LM contrast analysis facade

LM contrast analysis facade

Details

Encapsulates the pipeline: strategy_lm -> build_model -> Contrasts -> ContrastsModerated.

Public fields

model

Model object

contrast

ContrastsModerated object

Methods


Method new()

initialize

Usage

ContrastsLMFacade$new(lfqdata, modelstr, contrasts, ...)

Arguments

lfqdata

LFQData object

modelstr

model formula string (e.g. "~ group_")

contrasts

named character vector of contrasts

...

passed to strategy_lm


Method get_contrasts()

get contrast results

Usage

ContrastsLMFacade$get_contrasts(...)

Arguments

...

passed to ContrastsModerated$get_contrasts


Method get_Plotter()

get ContrastsPlotter

Usage

ContrastsLMFacade$get_Plotter(...)

Arguments

...

passed to ContrastsModerated$get_Plotter


Method to_wide()

convert results to wide format

Usage

ContrastsLMFacade$to_wide(...)

Arguments

...

passed to ContrastsModerated$to_wide


Method clone()

The objects of this class are cloneable with this method.

Usage

ContrastsLMFacade$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

istar <- sim_lfq_data_protein_config()
#> creating sampleName from fileName column
#> completing cases
#> completing cases done
#> setup done
lfqdata <- LFQData$new(istar$data, istar$config)
lfqdata$rename_response("transformedIntensity")
contrasts <- c("A_vs_Ctrl" = "group_A - group_Ctrl")
fa <- ContrastsLMFacade$new(lfqdata, "~ group_", contrasts)
#> Joining with `by = join_by(protein_Id)`
head(fa$get_contrasts())
#> determine linear functions:
#> Warning: linfct_matrix_contrasts: computed 0/2 contrasts; failed 2: A_vs_Ctrl, avg_A_vs_Ctrl.  In argument: `A_vs_Ctrl = group_A - group_Ctrl`.
#> Caused by error:
#> ! object 'group_Ctrl' not found;  In argument: `avg_A_vs_Ctrl = (group_A + group_Ctrl)/2`.
#> Caused by error:
#> ! object 'group_Ctrl' not found
#> get_contrasts -> contrasts_linfct
#> contrasts_linfct
#> Joining with `by = join_by(protein_Id, contrast)`
#> # A tibble: 6 × 14
#>   facade modelName  protein_Id contrast    diff std.error avgAbd statistic    df
#>   <chr>  <chr>      <chr>      <chr>      <dbl>     <dbl>  <dbl>     <dbl> <dbl>
#> 1 lm     WaldTest_… 0EfVhX~00… A_vs_Ct… -2.62       0.660   21.1   -3.51    15.1
#> 2 lm     WaldTest_… 7cbcrd~57… A_vs_Ct…  2.80       0.417   20.7    4.06    13.1
#> 3 lm     WaldTest_… 9VUkAq~47… A_vs_Ct…  1.67       0.740   20.3    1.97    14.1
#> 4 lm     WaldTest_… BEJI92~52… A_vs_Ct…  0.424      0.960   21.0    0.569   15.1
#> 5 lm     WaldTest_… CGzoYe~21… A_vs_Ct… -0.598      0.750   30.8   -0.867   16.1
#> 6 lm     WaldTest_… Fl4JiV~86… A_vs_Ct… -0.0494     0.603   21.3   -0.0664  15.1
#> # ℹ 5 more variables: p.value <dbl>, conf.low <dbl>, conf.high <dbl>,
#> #   sigma <dbl>, FDR <dbl>
fa$to_wide()
#> # A tibble: 9 × 5
#>   protein_Id  diff.A_vs_Ctrl p.value.A_vs_Ctrl FDR.A_vs_Ctrl statistic.A_vs_Ctrl
#>   <chr>                <dbl>             <dbl>         <dbl>               <dbl>
#> 1 0EfVhX~0087        -2.62             0.00311        0.0140             -3.51  
#> 2 7cbcrd~5725         2.80             0.00132        0.0119              4.06  
#> 3 9VUkAq~4703         1.67             0.0684         0.205               1.97  
#> 4 BEJI92~5282         0.424            0.578          0.650               0.569 
#> 5 CGzoYe~2147        -0.598            0.398          0.598              -0.867 
#> 6 Fl4JiV~8625        -0.0494           0.948          0.948              -0.0664
#> 7 HvIpHG~9079        -0.809            0.294          0.598              -1.09  
#> 8 JcKVfU~9653         0.642            0.365          0.598               0.932 
#> 9 SGIVBl~5782        -0.494            0.484          0.622              -0.717