Package: glyexp 0.14.1

Bin Fu

glyexp: Glycoproteomics and Glycomics Experiments

Provides a tidy data framework for managing glycoproteomics and glycomics experimental data. The core feature is the 'experiment()' class, which serves as a unified data container integrating expression matrices, variable information (proteins, peptides, glycan compositions, etc.), and sample metadata (groups, batches, clinical variables, etc.). The package enforces data consistency, validates column types according to experiment types (glycomics, glycoproteomics, traitomics, traitproteomics), and 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 a consistent interface that other packages can reliably extract information from, enabling smooth data exchange and analysis workflows.

Authors:Bin Fu [aut, cre, cph]

glyexp_0.14.1.tar.gz
glyexp_0.14.1.zip(r-4.7)glyexp_0.14.1.zip(r-4.6)glyexp_0.14.1.zip(r-4.5)
glyexp_0.14.1.tgz(r-4.6-any)glyexp_0.14.1.tgz(r-4.5-any)
glyexp_0.14.1.tar.gz(r-4.7-any)glyexp_0.14.1.tar.gz(r-4.6-any)
glyexp_0.14.1.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:

7.00 score 12 packages 53 scripts 50 exports 34 dependencies

Last updated from:3e3506a9b8 (on v0.14.1). Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK175
source / vignettesOK202
linux-release-x86_64OK178
macos-release-arm64OK150
macos-oldrel-arm64OK128
windows-develOK142
windows-releaseOK150
windows-oldrelOK129
wasm-releaseOK118

Exports:anti_join_obsanti_join_vararrange_obsarrange_varas_pseudo_glycomeas_seexperimentfilter_obsfilter_varfrom_seget_exp_typeget_expr_matget_glycan_typeget_meta_dataget_sample_infoget_var_infoinner_join_obsinner_join_varis_experimentleft_join_obsleft_join_varmutate_obsmutate_varn_samplesn_variablesrename_obsrename_varsamplesselect_obsselect_varsemi_join_obssemi_join_varset_exp_typeset_glycan_typeset_meta_dataslice_head_obsslice_head_varslice_max_obsslice_max_varslice_min_obsslice_min_varslice_obsslice_sample_obsslice_sample_varslice_tail_obsslice_tail_varslice_varstandardize_variablesummarize_experimentvariables

Dependencies:backportscheckmateclicodetoolscpp11digestdplyrfurrrfuturegenericsglobalsglueglyreprigraphlatticelifecyclelistenvmagrittrMatrixparallellypillarpkgconfigpurrrR6rlangrstackdequestringistringrtibbletidyrtidyselectutf8vctrswithr

Creating Experiments
Required Components | Step 1: Sample Information | Recommended Column Names | Step 2: Variable Information | Variable Naming | Column Conventions by Experiment Type | Step 3: Expression Matrix | Matching Requirements | Step 4: Creating the Experiment | Minimum Required Input
Rendered fromcreate-exp.Rmdusingknitr::rmarkdown

Last update: 2026-01-31
Started: 2025-09-23

dplyr-Style Functions: Data Harmony in Action
Core Philosophy: One Action, Three Updates | Two Flavors: _obs() and _var() | Filtering | Sample-Based Filtering with filter_obs() | Variable-Based Filtering with filter_var() | Chaining Filters | Index Columns: Guardians of Data Integrity | Attempting to Remove Index Columns | Why This Protection Matters | Complete Function Reference | Core Data Manipulation Functions | Advanced Slicing Functions | Joining Functions | Function-by-Function Examples | Selection | Arrangement | Mutation | Slicing | Renaming | Joining | Advanced Patterns: Chaining for Complex Operations | Pattern 1: Filter → Select → Arrange | Pattern 2: Mutate → Filter → Slice | Pattern 3: Random Sampling for Testing | 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-Experiment Objects | Pitfall 2: Forgetting the Synchronization | Pitfall 3: Trying to Remove Index Columns | Pitfall 4: Mismatched Operations | Performance Considerations | Philosophy Behind the Design | Summary
Rendered fromdplyr-style-functions.Rmdusingknitr::rmarkdown

Last update: 2026-01-31
Started: 2025-06-18

Experiment Types
Why Experiment Types Matter | The Four Experiment Types | Glycomics | Glycoproteomics | Traitomics | Traitproteomics | Do You Need to Worry About Experiment Types?
Rendered fromexp-type.Rmdusingknitr::rmarkdown

Last update: 2026-01-31
Started: 2025-09-21

Get Started with glyexp
Getting Started with glyexp | The Expression Matrix | Variable Information | Sample Information | Data Manipulation with glyexp | Complete dplyr Function Reference | Index Columns | Matrix-Style Subsetting | Merging and Splitting | Converting to Tibbles | Background and Design Principles | What's Next?
Rendered fromglyexp.Rmdusingknitr::rmarkdown

Last update: 2026-01-31
Started: 2025-06-16

Readme and manuals

Help Manual

Help pageTopics
Subsetting experiments[.glyexp_experiment [<-.glyexp_experiment
Arrange sample or variable informationarrange_obs arrange_var
Convert a glycoproteomics experiment to a pseudo-glycome experimentas_pseudo_glycome
Convert experiment to SummarizedExperimentas_se
Convert an experiment to a tibbleas_tibble.glyexp_experiment
Dimensions of an experimentdim.glyexp_experiment dim<-.glyexp_experiment
Dimname for experimentdimnames.glyexp_experiment
Create a new experimentexperiment is_experiment
Filter samples or variables of an experimentfilter_obs filter_var
Convert SummarizedExperiment to experimentfrom_se
Get the expression matrix of an experimentget_expr_mat
Get the meta data of an experimentget_exp_type get_glycan_type get_meta_data
Get the sample information of an experimentget_sample_info
Get the variable information of an experimentget_var_info
Join data to sample or variable informationanti_join_obs anti_join_var inner_join_obs inner_join_var left_join_obs left_join_var semi_join_obs semi_join_var
Merge two experimentsmerge.glyexp_experiment
Mutate sample or variable informationmutate_obs mutate_var
Get number of samples or variables of an experimentn_samples n_variables
Real glycoproteomics experimentreal_experiment
Real glycomics experimentreal_experiment2
Rename columns in the sample or variable information tibblerename_obs rename_var
Get Samples or Variables of an Experimentsamples variables
Select columns of the sample or variable information tibbleselect_obs select_var
Set the meta data of an experimentset_exp_type set_glycan_type set_meta_data
Slice sample or variable informationslice_head_obs slice_head_var slice_max_obs slice_max_var slice_min_obs slice_min_var slice_obs slice_sample_obs slice_sample_var slice_tail_obs slice_tail_var slice_var
Split an experimentsplit.glyexp_experiment
Standardize variable IDs in an experimentstandardize_variable
Identification overviewsummarize_experiment
Toy experimenttoy_experiment