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Sample metadata: group, cell type and clinical information

Source: R/metadata_cleaned.R
metadata_cleaned.Rd

Metadata of the 99 RNA-seq samples: 33 volunteers (10 healthy controls and 23 women with systemic lupus erythematosus, SLE), each contributing three cell types: monocytes (monocyte), monocyte-derived dendritic cells (moDC) and tolerogenic dendritic cells (tolDC). Clinical variables are repeated in the three samples of each volunteer.

Usage

metadata_cleaned

Format

A data frame with 99 rows (samples) and 14 columns. All columns are factors.

sample_ID

Sample identifier: volunteer ID plus cell type suffix (_0 = monocyte, _1 = moDC, _3 = tolDC; e.g., "QR011_1"). Also used as row names.

Group

Ctrl (healthy control) or SLE (patient).

GC

Glucocorticoid treatment: No or Si.

Dose

Glucocorticoid dose in mg (0, 2.5, 3, 5 or 8); 0 for controls and untreated patients.

Dose_category

Glucocorticoid treatment coded as 0 (no) or 1 (yes); equivalent to GC.

Age

Age in years.

Cell_type

Cell type: monocyte, moDC or tolDC.

Group_age

Age group: less30 (younger than 30 years) or more30 (30 years or older).

Nephritis

Lupus nephritis: No or Si; NA in controls.

Other_tx

Treatment other than glucocorticoids (e.g., antimalarials, immunosuppressants): No or Si; NA in controls.

Sledai_score

SLEDAI disease activity score (0 to 62); NA in controls.

Sledai_group

SLEDAI activity group: Without_activity, Low, Moderate, High or Very_high; NA in controls.

SLEDAI_Md

Yes/no indicator from the original clinical records (No, Si or Sí); NA in controls.

SLEDAI_category

Disease activity category: Zero (SLEDAI score 0, and all controls), No_activity (score 1-3) or Activity (score 4 or more).

Source

Hernández-Ledesma AL, Coss-Navarrete EL, et al. (2026), Front. Immunol. 17:1771959 (doi:10.3389/fimmu.2026.1771959 ); data and analysis code deposited in Zenodo (doi:10.5281/zenodo.17742206 ).

Details

  • Rows are in the same order as the columns of the count matrices of filtered_txi.

  • Age, Dose and Sledai_score are stored as factors; convert them with as.numeric(as.character(x)) before doing calculations.

  • The volunteer identifier (e.g., "QR011") is the prefix of sample_ID, sub("_.*", "", sample_ID); it links this table with volunteer_info.

  • In SLEDAI_Md, the "yes" level appears as Si and Sí; combine them before counting, for example with sub("Sí", "Si", SLEDAI_Md).

  • Sledai_score, Sledai_group and SLEDAI_category are groupings of disease activity used in the exploratory analyses. To describe the volunteers as in Table 1 of the article (age, treatments and active disease, SLEDAI 6 or more), use volunteer_info, which has one row per volunteer, as in the lessons.

See also

filtered_txi, volunteer_info

Examples

head(metadata_cleaned)
#>         sample_ID Group GC Dose Dose_category Age Cell_type Group_age Nephritis
#> QR011_0   QR011_0  Ctrl No    0             0  25  monocyte    less30      <NA>
#> QR011_1   QR011_1  Ctrl No    0             0  25      moDC    less30      <NA>
#> QR011_3   QR011_3  Ctrl No    0             0  25     tolDC    less30      <NA>
#> QR013_0   QR013_0  Ctrl No    0             0  23  monocyte    less30      <NA>
#> QR013_1   QR013_1  Ctrl No    0             0  23      moDC    less30      <NA>
#> QR013_3   QR013_3  Ctrl No    0             0  23     tolDC    less30      <NA>
#>         Other_tx Sledai_score Sledai_group SLEDAI_Md SLEDAI_category
#> QR011_0     <NA>         <NA>         <NA>      <NA>            Zero
#> QR011_1     <NA>         <NA>         <NA>      <NA>            Zero
#> QR011_3     <NA>         <NA>         <NA>      <NA>            Zero
#> QR013_0     <NA>         <NA>         <NA>      <NA>            Zero
#> QR013_1     <NA>         <NA>         <NA>      <NA>            Zero
#> QR013_3     <NA>         <NA>         <NA>      <NA>            Zero
table(metadata_cleaned$Group, metadata_cleaned$Cell_type)
#>       
#>        moDC monocyte tolDC
#>   Ctrl   10       10    10
#>   SLE    23       23    23

# Age as a number
summary(as.numeric(as.character(metadata_cleaned$Age)))
#>    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
#>   19.00   25.00   34.00   32.21   38.00   47.00