Package: glyexp 0.18.0

Bin Fu

glyexp: Glycoproteomics and Glycomics Experiments

Provides a tidy data framework for managing glycoproteomics and glycomics experimental data. The 'GlycomicSE' and 'GlycoproteomicSE' classes extend 'SummarizedExperiment' with validated glycomics and glycoproteomics schemas. The package provides dplyr-style data manipulation functions (filter, mutate, select, arrange, slice, join) for seamless data wrangling. As the data core of the 'glycoverse' ecosystem, it provides consistent interfaces for data exchange and analysis workflows.

Authors:Bin Fu [aut, cre, cph]

glyexp_0.18.0.tar.gz
glyexp_0.18.0.zip(r-4.7-any)glyexp_0.18.0.zip(r-4.6-any)glyexp_0.18.0.zip(r-4.5-any)
glyexp_0.18.0.tgz(r-4.6-any)glyexp_0.18.0.tgz(r-4.5-any)
glyexp_0.18.0.tar.gz(r-4.7-any)glyexp_0.18.0.tar.gz(r-4.6-any)
glyexp_0.18.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
glyexp/json (API)

# Install 'glyexp' in R:
install.packages('glyexp', repos = c('https://glycoverse.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/glycoverse/glyexp/issues

Pkgdown/docs site:https://glycoverse.github.io

Datasets:

On CRAN:

Conda:

6.58 score 8 packages 44 scripts 98 exports 42 dependencies

Last updated from:b4635c759f (on v0.18.0). Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK257
source / vignettesOK790
linux-releaseOK249
macos-releaseOK192
macos-oldrelOK193
windows-develOK232
windows-releaseOK219
windows-oldrelOK212
wasm-releaseOK112

Exports:.GlycomicSE.GlycoproteomicSEanti_join_colanti_join_obsanti_join_rowanti_join_vararrange_colarrange_obsarrange_rowarrange_varas_glycomic_seas_glycoproteomic_seas_pseudo_glycomeas_pseudo_glycomesas_seassayassay<-colDatacolData<-experimentfilter_colfilter_obsfilter_rowfilter_varfrom_seget_exp_typeget_expr_matget_glycan_typeget_meta_dataget_sample_infoget_var_infoGlycomicSEGlycoproteomicSEinner_join_colinner_join_obsinner_join_rowinner_join_varis_experimentis_glycomic_seis_glycoproteomic_seleft_join_colleft_join_obsleft_join_rowleft_join_varmetadatametadata<-mutate_colmutate_obsmutate_rowmutate_varn_samplesn_variablesrename_colrename_obsrename_rowrename_varrowDatarowData<-samplesselect_colselect_obsselect_rowselect_varsemi_join_colsemi_join_obssemi_join_rowsemi_join_varset_exp_typeset_glycan_typeset_meta_datashowslice_colslice_head_colslice_head_obsslice_head_rowslice_head_varslice_max_colslice_max_obsslice_max_rowslice_max_varslice_min_colslice_min_obsslice_min_rowslice_min_varslice_obsslice_rowslice_sample_colslice_sample_obsslice_sample_rowslice_sample_varslice_tail_colslice_tail_obsslice_tail_rowslice_tail_varslice_varstandardize_variablesummarize_experimentvariables

Dependencies:abindbackportsBiobaseBiocGenericscheckmateclicpp11DelayedArraydplyrgenericsGenomicRangesglueglyreprigraphIRangeslatticelifecyclemagrittrMatrixMatrixGenericsmatrixStatspillarpkgconfigpurrrR6RcpprlangrstackdequeS4ArraysS4VectorsSeqinfoSparseArraystringistringrSummarizedExperimenttibbletidyrtidyselectutf8vctrswithrXVector

Creating Experiments
Required Components | Step 1: Sample Information (Column Data) | Step 2: Variable Information (Row Data) | Step 3: Expression Matrix | Matching Requirements | Step 4: Creating the Experiment
Rendered fromcreate-exp.Rmdusingknitr::rmarkdown

Last update: 2026-07-27
Started: 2025-09-23

dplyr-Style Functions
Two Flavors: _col() and _row() | Virtual Index Columns | Complete Function Reference | Core Data Manipulation Functions | Advanced Slicing Functions | Joining Functions | Function-by-Function Examples | Selection | Arrangement | Mutation | Slicing | Renaming | Joining | When dplyr-Style Functions Cannot Help | Why Doesn't glyexp Implement All dplyr Functions? | Common Pitfalls and How to Avoid Them | Pitfall 1: Using glyexp Functions on Non-SE Objects | Pitfall 2: Forgetting the Synchronization | Pitfall 3: Trying to Remove Index Columns | Pitfall 4: Mismatched Operations | Performance Considerations | Philosophy Behind the Design
Rendered fromdplyr-style-functions.Rmdusingknitr::rmarkdown

Last update: 2026-07-27
Started: 2025-06-18

Get Started with glyexp
For those familiar with SummarizedExperiment | Getting Started with glyexp | The Expression Matrix | Variable Information | Sample Information | Rownames and colnames | Data Manipulation with glyexp | Background and Design Principles | What's Next?
Rendered fromglyexp.Rmdusingknitr::rmarkdown

Last update: 2026-07-27
Started: 2025-06-16

Readme and manuals

Help Manual

Help pageTopics
Arrange sample or variable informationarrange_col arrange_row
Coerce to GlycomicSEas_glycomic_se is_glycomic_se
Coerce to GlycoproteomicSEas_glycoproteomic_se is_glycoproteomic_se
Convert a glycoproteomics experiment to a pseudo-glycome experimentas_pseudo_glycome
Convert a glycoproteomics experiment to pseudo-glycomesas_pseudo_glycomes
Convert a glycomics container to a long-format tibbleas_tibble.GlycomicSE as_tibble.GlycoproteomicSE
Filter samples or variables of an experimentfilter_col filter_row
Create a GlycomicSE objectGlycomicSE GlycomicSE-class
Create a GlycoproteomicSE objectGlycoproteomicSE GlycoproteomicSE-class
Join data to sample or variable informationanti_join_col anti_join_row inner_join_col inner_join_row left_join_col left_join_row semi_join_col semi_join_row
Mutate sample or variable informationmutate_col mutate_row
Real glycoproteomics experimentreal_experiment
Real glycomics experimentreal_experiment2
Rename columns in the sample or variable information tibblerename_col rename_row
Select columns of the sample or variable information tibbleselect_col select_row
Slice sample or variable informationslice_col slice_head_col slice_head_row slice_max_col slice_max_row slice_min_col slice_min_row slice_row slice_sample_col slice_sample_row slice_tail_col slice_tail_row
Standardize variable IDs in an experimentstandardize_variable
Identification overviewsummarize_experiment