fix: metadata, remove unused parameter

Author: vadimnazarov

.github/workflows/ci.yml

@@ -27,11 +27,12 @@ jobs:
       - run: pip install mkdocs-material mkquartodocs mkdocs-static-i18n
 
       - uses: r-lib/actions/setup-r@v2
+        with:
+          use-public-rspm: true
 
       - name: Install immunarch and immundata
         uses: r-lib/actions/setup-r-dependencies@v2
         with:
-          use-public-rspm: true
           upgrade: 'TRUE' 
           packages: |
             any::Seurat

docs/source/howto/read_airr_bulk.md

@@ -24,28 +24,28 @@ Use this for bulk AIRR Rearrangement TSVs (one row per rearrangement/receptor).
     schema <- make_receptor_schema(features = c("cdr3_aa", "v_call"))
 
     idata <- read_repertoires(
-      path      = "/path/to/bulk_airr/*.tsv",
-      schema    = schema,
-      count_col = "umi_count",
+      path       = "/path/to/bulk_airr/*.tsv",
+      schema     = schema,
+      count_col  = "umi_count",
       preprocess = make_default_preprocessing("airr")
     )
 
     # If you have metadata, you can use it:
     idata <- read_repertoires(
-      path      = "/path/to/bulk_airr/*.tsv",
-      metadata  = your_metadata_table,
-      schema    = schema,
-      count_col = "umi_count",
+      path       = "/path/to/bulk_airr/*.tsv",
+      metadata   = your_metadata_table,
+      schema     = schema,
+      count_col  = "umi_count",
       preprocess = make_default_preprocessing("airr")
     )
 
     # If you already know the repertoire schema:
     idata <- read_repertoires(
-      path      = "/path/to/bulk_airr/*.tsv",
-      metadata  = your_metadata_table,
-      schema    = schema,
-      count_col = "umi_count",
-      preprocess = make_default_preprocessing("airr"),
+      path              = "/path/to/bulk_airr/*.tsv",
+      metadata          = your_metadata_table,
+      schema            = schema,
+      count_col         = "umi_count",
+      preprocess        = make_default_preprocessing("airr"),
       repertoire_schema = c("Patient", "Cluster", "Response")
     )
     ```

docs/source/howto/read_airr_sc.md

@@ -39,7 +39,7 @@ Use this when your single-cell data export is AIRR-C and includes cell barcodes
     idata <- read_repertoires(
       path        = "/path/to/sc_airr/*.tsv",
       schema      = schema,
-      metadata  = your_metadata_table,
+      metadata    = your_metadata_table,
       barcode_col = "cell_id",
       locus_col   = "locus",
       umi_col     = "umi_count",
@@ -48,13 +48,13 @@ Use this when your single-cell data export is AIRR-C and includes cell barcodes
 
     # If you already know the repertoire schema:
     idata <- read_repertoires(
-      path        = "/path/to/sc_airr/*.tsv",
-      schema      = schema,
-      metadata  = your_metadata_table,
-      barcode_col = "cell_id",
-      locus_col   = "locus",
-      umi_col     = "umi_count",
-      preprocess  = make_default_preprocessing("airr"),
+      path              = "/path/to/sc_airr/*.tsv",
+      schema            = schema,
+      metadata          = your_metadata_table,
+      barcode_col       = "cell_id",
+      locus_col         = "locus",
+      umi_col           = "umi_count",
+      preprocess        = make_default_preprocessing("airr"),
       repertoire_schema = c("Patient", "Cluster", "Response")
     )
     ```