Calculate Derived Traits from Tidy Data

This function calculates derived traits from a tibble in tidy format. Use this function if you are not using the glyexp package. For glycomics data, it calculates the derived traits directly. For glycoproteomics data, each glycosite is treated as a separate glycome, and derived traits are calculated in a site-specific manner.

Usage

derive_traits_(tbl, data_type, trait_fns = NULL, mp_fns = NULL)

Arguments

tbl

A tibble in tidy format, with the following columns:

• sample: sample ID

• glycan_structure: glycan structures, either a glyrepr::glycan_structure() vector or a character vector of glycan structure strings supported by glyparse::auto_parse().

• value: the quantification of the glycan in the sample.

For glycoproteomics data, additional columns are needed:

• protein: protein ID

• protein_site: the glycosite position on the protein The unique combination of protein and protein_site determines a glycosite.

Other columns are ignored.

Please make sure that the data has been properly preprocessed, including normalization, missing value handling, etc. Specifically, for glycoproteomics data, please make sure that the data has been aggregated to the "glycoforms with structures" level. That is the quantification of each glycan structure on each glycosite in each sample.

data_type

Either "glycomics" or "glycoproteomics".

trait_fns

A named list of derived trait functions created by trait factories. Names of the list are the names of the derived traits. Default is NULL, which means all derived traits in basic_traits() are calculated.

mp_fns

A named list of meta-property functions. This parameter is useful if your trait functions use custom meta-properties other than those in all_mp_fns(). Default is NULL, which means all meta-properties in all_mp_fns() are used.

Value

A tidy tibble containing the following columns:

• sample: sample ID

• trait: derived trait name

• value: the value of the derived trait

For glycoproteomics data, with additional columns:

• protein: protein ID

• protein_site: the glycosite position on the protein

Other columns in the original tibble are not included.

See also

derive_traits(), basic_traits(), all_traits()

Examples

# Create example tidy data
library(dplyr)
#> 
#> Attaching package: ‘dplyr’
#> The following object is masked from ‘package:glyexp’:
#> 
#>     select_var
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union
library(glyexp)
library(tibble)

tidy_data <- as_tibble(real_experiment2)

# Calculate traits
traits <- derive_traits_(tidy_data, data_type = "glycomics")
traits
#> # A tibble: 2,016 × 3
#>    trait sample  value
#>    <chr> <chr>   <dbl>
#>  1 TM    S1     0.0322
#>  2 TM    S2     0.0274
#>  3 TM    S3     0.0215
#>  4 TM    S4     0.0178
#>  5 TM    S5     0.0238
#>  6 TM    S6     0.0254
#>  7 TM    S7     0.0234
#>  8 TM    S8     0.0200
#>  9 TM    S9     0.0170
#> 10 TM    S10    0.0207
#> # ℹ 2,006 more rows