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Retrieving Results from Sirius

Source: vignettes/RetrievingResults.Rmd
RetrievingResults.Rmd

Introduction

Note: This vignette code is not evaluated during package checks as it requires a running Sirius instance with completed computations.

After running Sirius computations (see the “Importing Spectra” vignette), you can retrieve various types of results. RuSirius provides two main functions:

  • summary() - Quick overview of top results per feature
  • results() - Detailed results with multiple candidates

Connecting to a Project

First, connect to an existing Sirius project that has completed computations:

srs <- Sirius(projectId = "my_analysis", path = getwd(), port = 9999)

Quick Summary with summary()

The summary() function provides the top annotation for each feature. This is useful for a quick overview of your results.

Formula Identification Summary 

# Top formula candidates
summary_formula <- summary(srs, result.type = "formulaId")
head(summary_formula)

Key columns include confidenceApproxMatch (overall confidence for the feature) and confidenceExactMatch (confidence for the top hit).

Structure Database Summary 

# Top structure hits
summary_structure <- summary(srs, result.type = "structure")

De Novo Structure Summary 

# Top MSNovelist predictions
summary_denovo <- summary(srs, result.type = "deNovo")

Spectral Library Match Summary 

# Best spectral matches
summary_spectral <- summary(srs, result.type = "spectralDbMatch")

Detailed Results with results()

The results() function returns multiple candidates per feature, giving you more options to explore.

Formula Candidates 

# Get top 5 formula candidates per feature
formulas <- results(srs,
                    result.type = "formulaId",
                    topFormula = 5,
                    return.type = "data.frame")
head(formulas)

Structure Database Results 

# Get structure candidates for each formula
structures <- results(srs,
                      result.type = "structureDb",
                      topFormula = 3,
                      topStructure = 5,
                      return.type = "data.frame")

Key columns: inchiKey, smiles, structureName, csiScore.

Compound Class Predictions (CANOPUS) 

# Get predicted compound classes
classes <- results(srs,
                   result.type = "compoundClass",
                   topFormula = 1,
                   return.type = "data.frame")

Returns ClassyFire and NPC classifications with confidence scores.

De Novo Structures (MSNovelist) 

# Get de novo predicted structures
denovo <- results(srs,
                  result.type = "deNovo",
                  topFormula = 1,
                  topStructure = 5,
                  return.type = "data.frame")

Spectral Library Matches 

# Get spectral library matches
spectral <- results(srs,
                    result.type = "spectralDbMatch",
                    topSpectralMatches = 5,
                    return.type = "data.frame")

Fragmentation Trees 

# Get fragmentation tree data
fragtrees <- results(srs,
                     result.type = "fragTree",
                     topFormula = 1,
                     return.type = "data.frame")

Filtering by Feature

You can retrieve results for specific features only:

# Get feature IDs
feature_ids <- featuresId(srs)

# Get results for first two features only
subset_results <- results(srs,
                          features = feature_ids[1:2],
                          result.type = "structureDb",
                          return.type = "data.frame")

Return Types

Results can be returned as a data.frame (default) or as a list:

# As list - useful for per-feature processing
results_list <- results(srs,
                        result.type = "formulaId",
                        return.type = "list")

# Access results for a specific feature
results_list[["feature_id_here"]]

Mapping to Original IDs

If you imported data from xcms, results include the original xcms feature IDs in the xcms_fts column for easy mapping back to your original data.

# Get the feature mapping
mapFeatures(srs)

Session Info 

## R version 4.5.2 (2025-10-31)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 24.04.3 LTS
## 
## Matrix products: default
## BLAS:   /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3 
## LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.26.so;  LAPACK version 3.12.0
## 
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##  [7] LC_PAPER=C.UTF-8       LC_NAME=C              LC_ADDRESS=C          
## [10] LC_TELEPHONE=C         LC_MEASUREMENT=C.UTF-8 LC_IDENTIFICATION=C   
## 
## time zone: UTC
## tzcode source: system (glibc)
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
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## other attached packages:
## [1] BiocStyle_2.38.0
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## loaded via a namespace (and not attached):
##  [1] digest_0.6.39       desc_1.4.3          R6_2.6.1           
##  [4] bookdown_0.46       fastmap_1.2.0       xfun_0.56          
##  [7] cachem_1.1.0        knitr_1.51          htmltools_0.5.9    
## [10] rmarkdown_2.30      lifecycle_1.0.5     cli_3.6.5          
## [13] sass_0.4.10         pkgdown_2.2.0       textshaping_1.0.5  
## [16] jquerylib_0.1.4     systemfonts_1.3.2   compiler_4.5.2     
## [19] tools_4.5.2         ragg_1.5.1          bslib_0.10.0       
## [22] evaluate_1.0.5      yaml_2.3.12         BiocManager_1.30.27
## [25] otel_0.2.0          jsonlite_2.0.0      rlang_1.1.7        
## [28] fs_1.6.7            htmlwidgets_1.6.4