my proposed changes

.travis.yml

@@ -19,11 +19,10 @@ install:
   - conda config --add channels defaults
   - conda config --add channels conda-forge
   - conda config --add channels bioconda
-  - conda install -c bioconda -c conda-forge snakemake
-  - conda create -q -n snakemake snakemake>=5.3.1 python=3.6
+  - conda create -q -n snakemake 'snakemake>=5.3.1' 'python>=3.10'
 
 script:
-  - python3.6 setup.py install
+  - pip install .
   - pytest
 
 after_success:

cite_seq_count/__main__.py

@@ -94,6 +94,8 @@ def main():
         print("Skipping cell barcode correction")
         bcs_corrected = 0
 
+    ###### HERE IT STOPS WORKING ##########
+
     # Create sparse matrices for reads results
     read_results_matrix = processing.generate_sparse_matrices(
         final_results=final_results,

cite_seq_count/preprocessing.py

@@ -57,7 +57,7 @@ def parse_barcode_reference(
     barcode_pattern = rf"^[ATGC]{{{barcode_length}}}"
 
     header = barcodes_pl.columns
-    set_dif = set(required_header) - set(header)
+    set_dif = set([required_header]) - set(header)
     if len(set_dif) != 0:
         set_diff_string = ",".join(list(set_dif))
         raise SystemExit(f"The header is missing {set_diff_string}. Exiting")
@@ -74,7 +74,7 @@ def parse_barcode_reference(
 
     else:
         barcodes_pl = barcodes_pl.with_columns(
-            reference=pl.col(REFERENCE_COLUMN).str.strip_chars(STRIP_CHARS),
+            reference=pl.col(required_header).str.strip_chars(STRIP_CHARS),
         )
 
     check_sequence_pattern(
@@ -110,7 +110,7 @@ def parse_tags_csv(file_name: str) -> pl.DataFrame:
         TTCCGCCTCTCTTTG,Hashtag_3
 
     Args:
-        file_name (str): file path as a tring
+        file_name (str): file path as a string
 
     Returns:
         pl.DataFrame: polars dataframe with the csv content
@@ -381,16 +381,17 @@ def get_barcode_subset(
     enable_barcode_correction = True
     if barcode_whitelist:
         barcode_subset = parse_barcode_reference(
-            filename=expected_barcodes,
+            filename=barcode_whitelist,
             barcode_length=(chemistry.cell_barcode_end - chemistry.cell_barcode_start),
             required_header=WHITELIST_COLUMN,
         )
+        n_barcodes = len(barcode_subset) # ???
     else:
-        n_barcodes = barcode_whitelist
+        n_barcodes = expected_barcodes
         if barcode_reference is not None:
             barcode_subset = (
                 barcodes_df.filter(
-                    pl.col(BARCODE_COLUMN).str.is_in(
+                    pl.col(BARCODE_COLUMN).is_in(
                         barcode_reference[REFERENCE_COLUMN]
                     )
                 )
@@ -399,7 +400,7 @@ def get_barcode_subset(
                 .sort("count", descending=True)
                 .head(n_barcodes * 1.2)
                 .drop("count")
-                .rename({SEQUENCE_COLUMN: WHITELIST_COLUMN})
+                .rename({BARCODE_COLUMN: WHITELIST_COLUMN})
             )
         else:
             raw_barcodes_dict = (

setup.py

@@ -33,7 +33,8 @@
         "pyyaml==6.0",
         "pooch==1.6.0",
         "six==1.16.0",
+        "polars"
     ],
-    python_requires=">=3.8",
+    python_requires=">=3.10",
     package_data={"report_template": ["templates/*.json"]},
 )

tests/test_data/tags/pass/correct_3.csv

@@ -0,0 +1,5 @@
+sequence,feature_name
+CGTACGTAGCCTAGC,test1
+CGTAGCTCGAAAAAA,test2
+CGTCGAAGCTGAACG,test3
+CGTCGTAGCTGATCG,test4

tests/test_data/whitelist.csv

@@ -0,0 +1,3 @@
+whitelist
+TACATATTCTTTACTG
+TAGAGGGAAGTCAAGC