Merge pull request #14 from klarman-cell-observatory/boli

Multiple small changes.

pegasusio/hdf5_utils.py

@@ -256,7 +256,6 @@ def _process_attrs(key_name: str, attrs: pd.DataFrame, attrs_multi: dict) -> Dic
         layers["" if matkey == "X" else matkey] = data.get_matrix(matkey).T
 
     file_attrs = {}
-    print(type(data.uns))
     for key, value in data.uns.items():
         if isinstance(value, str):
             file_attrs[key] = value

pegasusio/readwrite.py

@@ -97,7 +97,7 @@ def read_input(
 ) -> MultimodalData:
     """Load data into memory.
 
-    This function is used to load input data into memory. Inputs can be in 10x genomics v2 & v3 formats (hdf5 or mtx), HCA DCP mtx and csv formats, Drop-seq dge format, and CSV format.
+    This function is used to load input data into memory. Inputs can be in 'zarr', 'h5ad', 'loom', '10x', 'mtx', 'csv', 'tsv' or 'fcs' (for flow/mass cytometry data) formats.
 
     Parameters
     ----------

pegasusio/text_utils.py

@@ -153,7 +153,7 @@ def load_one_mtx_file(path: str, file_name: str, genome: str, modality: str) ->
     mat = csr_matrix((data, (row_ind, col_ind)), shape = shape)
     mat.eliminate_zeros()
 
-    unidata = UnimodalData(barcode_metadata, feature_metadata, {"X": mat}, {"modality": modality, "genome": genome})
+    unidata = UnimodalData(barcode_metadata, feature_metadata, {"X": mat}, {"genome": genome, "modality": modality})
     if format_type == "10x v3" or format_type == "10x v2":
         unidata.separate_channels()
 
@@ -173,7 +173,7 @@ def _locate_mtx_file(path: str) -> str:
     return file_names[0] if len(file_names) > 0 else None
 
 
-def load_mtx_file(path: str, genome: str = None, modality: str = None, ngene: int = None) -> MultimodalData:
+def load_mtx_file(path: str, genome: str = None, modality: str = None) -> MultimodalData:
     """Load gene-count matrix from Market Matrix files (10x v2, v3 and HCA DCP formats)
 
     Parameters
@@ -185,8 +185,6 @@ def load_mtx_file(path: str, genome: str = None, modality: str = None, ngene: in
         Genome name of the matrix. If None, genome will be inferred from path.
     modality: `str`, optional (default: None)
         Modality, choosing from 'rna', 'citeseq', 'hashing', 'tcr', 'bcr', 'crispr' or 'atac'. If None, use 'rna' as default.
-    ngene : `int`, optional (default: None)
-        Minimum number of genes to keep a barcode. Default is to keep all barcodes. Only apply to 'rna' modality
 
     Returns
     -------
@@ -218,13 +216,11 @@ def load_mtx_file(path: str, genome: str = None, modality: str = None, ngene: in
         if genome is None:
             genome = os.path.basename(path)
         data.add_data(
-            genome,
             load_one_mtx_file(
                 path,
                 file_name,
                 genome,
-                modality,
-                ngene=ngene,
+                modality
             ),
         )
     else:
@@ -233,7 +229,7 @@ def load_mtx_file(path: str, genome: str = None, modality: str = None, ngene: in
                 file_name = _locate_mtx_file(dir_entry.path)
                 if file_name is None:
                     raise ValueError(f"Folder {dir_entry.path} does not contain a mtx file!")
-                data.add_data(dir_entry.name, load_one_mtx_file(dir_entry.path, file_name, dir_entry.name, modality, ngene=ngene))
+                data.add_data(load_one_mtx_file(dir_entry.path, file_name, dir_entry.name, modality))
 
     return data