Concrete subclass for FGCZ proteomics SummarizedExperiment outputs

Reads from a prolfqua-derived SE. Top-level rowData(se) is sparse; feature metadata and per-contrast DE statistics live nested inside rowData(se)$constrast_<name> DataFrames (note the SUSHI typo is preserved). The first contrast is the source of truth for feature metadata. feature_id is built from protein_Id (+ site / peptide_Id to disambiguate), and the assay matrices' rownames are remapped via .fid_lookup since SE rownames do not match the built feature_ids.

Value

An R6 class generator; $new() returns an ExploreDatasetSE_Proteomics object.

Details

Inherits the accessor contract from ExploreDataset via ExploreDatasetSE; overrides .build_config() and .prep().

Super classes

ExploreDataset -> ExploreDatasetSE -> ExploreDatasetSE_Proteomics

Methods

Public methods

• ExploreDatasetSE_Proteomics$clone()

Inherited methods

• ExploreDataset$all_pathways()
• ExploreDataset$assay_label()
• ExploreDataset$background_expression()
• ExploreDataset$contrast_label()
• ExploreDataset$contrast_meta()
• ExploreDataset$contrasts()
• ExploreDataset$data_type()
• ExploreDataset$de_all()
• ExploreDataset$de_display_extras()
• ExploreDataset$enrichment_filter()
• ExploreDataset$enrichment_kinds()
• ExploreDataset$enrichment_table()
• ExploreDataset$factor_levels()
• ExploreDataset$factor_names()
• ExploreDataset$feature_display()
• ExploreDataset$feature_id_kind()
• ExploreDataset$feature_ids()
• ExploreDataset$format()
• ExploreDataset$has_assay()
• ExploreDataset$has_de()
• ExploreDataset$has_enrichment()
• ExploreDataset$has_pvalue()
• ExploreDataset$n_features()
• ExploreDataset$n_samples()
• ExploreDataset$omics_class()
• ExploreDataset$organism()
• ExploreDataset$primary_assay()
• ExploreDataset$primary_assay_name()
• ExploreDataset$primary_contrast()
• ExploreDataset$primary_grouping()
• ExploreDataset$proteomics_choices()
• ExploreDataset$raw_assay()
• ExploreDataset$raw_assay_name()
• ExploreDataset$ref_build()
• ExploreDataset$sample_factor()
• ExploreDataset$sample_ids()
• ExploreDataset$secondary_grouping()
• ExploreDataset$sgrna_to_gene()
• ExploreDataset$source()
• ExploreDatasetSE$assay()
• ExploreDatasetSE$assay_names()
• ExploreDatasetSE$backend()
• ExploreDatasetSE$backend_kind()
• ExploreDatasetSE$de()
• ExploreDatasetSE$enrichment()
• ExploreDatasetSE$enrichment_input()
• ExploreDatasetSE$features()
• ExploreDatasetSE$initialize()
• ExploreDatasetSE$samples()

---

ExploreDatasetSE_Proteomics$clone()

The objects of this class are cloneable with this method.

Usage

ExploreDatasetSE_Proteomics$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

se <- readRDS(system.file("examples/proteomics/SummarizedExperiment.rds", package = "exploreDE"))
eds <- ExploreDatasetSE_Proteomics$new(se)
eds
#> <ExploreDatasetSE_Proteomics  (se)>
#>   data_type:        proteomics
#>   feature_id_kind:  protein
#>   organism:         NA
#>   ref_build:        NA
#>   samples x features: 6 x 1384
#>   factors (3):
#>     G_  (primary): A, B
#>     CONTROL: C, T
#>     isotopeLabel: light
#>   contrasts (1): B_vs_A
#>   primary_contrast: B_vs_A
#>   assays:           intensities
#>   enrichment:       (none)
head(eds$feature_ids())
#> [1] "A0A0U1RRI6" "A1L429"     "A2RU48"     "A6NCE7"     "A6NEC2"    
#> [6] "A6NEK1"    
head(eds$de(eds$primary_contrast()))
#>        nrPeptides IDcolumn              fasta.id           description
#> P0AFG3         25   P0AFG3  sp|P0AFG3|ODO1_ECOLI  sp_P0AFG3_ODO1_ECOLI
#> P0AC41         15   P0AC41  sp|P0AC41|SDHA_ECOLI  sp_P0AC41_SDHA_ECOLI
#> P0A7W1          5   P0A7W1   sp|P0A7W1|RS5_ECOLI   sp_P0A7W1_RS5_ECOLI
#> P0A7V0          8   P0A7V0   sp|P0A7V0|RS2_ECOLI   sp_P0A7V0_RS2_ECOLI
#> A1L429          1   A1L429 sp|A1L429|GG12C_HUMAN sp_A1L429_GG12C_HUMAN
#> P0AFG6         10   P0AFG6  sp|P0AFG6|ODO2_ECOLI  sp_P0AFG6_ODO2_ECOLI
#>        protein_length nr_tryptic_peptides   CON   REV              modelName
#> P0AFG3            933                  44 FALSE FALSE Linear_Model_moderated
#> P0AC41            588                  31 FALSE FALSE Linear_Model_moderated
#> P0A7W1            167                  11 FALSE FALSE Linear_Model_moderated
#> P0A7V0            241                  14 FALSE FALSE Linear_Model_moderated
#> A1L429            117                   2 FALSE FALSE Imputed_Mean_moderated
#> P0AFG6            405                  20 FALSE FALSE Linear_Model_moderated
#>        contrast log2Ratio  std.error   avgAbd statistic       df       pValue
#> P0AFG3   B_vs_A  2.076169 0.02592986 19.27265  26.95160 5.832013 2.407749e-07
#> P0AC41   B_vs_A  2.207672 0.05267450 19.16701  25.70541 5.832013 3.166968e-07
#> P0A7W1   B_vs_A  2.232960 0.05541211 21.40682  25.64938 5.832013 3.207217e-07
#> P0A7V0   B_vs_A  2.290956 0.06851577 20.84410  24.57190 5.832013 4.111082e-07
#> A1L429   B_vs_A -7.134870 0.06665272 21.11332 -68.04320 3.798723 5.272144e-07
#> P0AFG6   B_vs_A  2.690083 0.11613502 20.00267  22.16970 5.832013 7.449241e-07
#>         conf.low conf.high      sigma          fdr feature_id effect_log2fc
#> P0AFG3  1.843691  2.308647 0.09434608 0.0001329935     P0AFG3      2.076169
#> P0AC41  1.948485  2.466860 0.10518546 0.0001329935     P0AC41      2.207672
#> P0A7W1  1.970231  2.495689 0.10662272 0.0001329935     P0A7W1      2.232960
#> P0A7V0  2.009583  2.572328 0.11418883 0.0001329935     P0A7V0      2.290956
#> A1L429 -7.499009 -6.770731 0.12842423 0.0001459329     A1L429     -7.134870
#> P0AFG6  2.323891  3.056276 0.14861122 0.0001562791     P0AFG6      2.690083
#>        score_pvalue    score_fdr usedInTest
#> P0AFG3 2.407749e-07 0.0001329935       TRUE
#> P0AC41 3.166968e-07 0.0001329935       TRUE
#> P0A7W1 3.207217e-07 0.0001329935       TRUE
#> P0A7V0 4.111082e-07 0.0001329935       TRUE
#> A1L429 5.272144e-07 0.0001459329       TRUE
#> P0AFG6 7.449241e-07 0.0001562791       TRUE