update README and docs

README.md

@@ -57,13 +57,13 @@ files = os.listdir(bw_dir)
 bw_files = [f"{bw_dir}/{f}" for f in files]
 
 features = pd.DataFrame({
-     "chrom": ["chr1", "chr1"],
-     "start": [1000, 2000],
-     "end": [1500, 2500]
+     "seqnames": ["chr1", "chr1"],
+     "starts": [1000, 2000],
+     "ends": [1500, 2500]
 })
 
 # Build GenomicArray
-garr.build_genomicarray(
+dataset = garr.build_genomicarray(
      files=bw_files,
      output_path=tempdir,
      features=features,
@@ -80,6 +80,48 @@ garr.build_genomicarray(
 The build process stores missing intervals from a bigwig file as `np.nan`. The
 default is to choose an aggregate functions that works with `np.nan`.
 
+### Query a `GenomicArrayDataset`
+
+Users have the option to reuse the `dataset` object retuned when building the arrays or by creating a `GenomicArrayDataset` object by initializing it to the path where the files were created.
+
+```python
+# Create a GenomicArrayDataset object from the existing dataset
+dataset = GenomicArrayDataset(dataset_path=tempdir)
+
+# Query data for the first 10 regions across all samples
+coverage_data = dataset[0:10, :]
+
+print(expression_data.matrix)
+print(expression_data.feature_annotation)
+```
+
+     ## output 1
+     array([[1. , 0.5],
+          [1. , 0.5],
+          [1. , 0.5],
+          [1. , 0.5],
+          [1. , 0.5],
+          [1. , 0.5],
+          [1. , 0.5],
+          [1. , 0.5],
+          [1. , 0.5],
+          [1. , 0.5],
+          [1. , nan]], dtype=float32)
+
+     ## output 2
+     seqnames  starts  ends  genarr_feature_index
+     0      chr1     300   315                     0
+     1      chr1     320   335                     1
+     2      chr1     340   355                     2
+     3      chr1     360   375                     3
+     4      chr1     380   395                     4
+     5      chr1     400   415                     5
+     6      chr1     420   435                     6
+     7      chr1     440   455                     7
+     8      chr1     460   475                     8
+     9      chr1     480   495                     9
+     10     chr1     500   515                    10
+
 
 <!-- pyscaffold-notes -->
 

src/genomicarrays/GenomicArrayDataset.py

@@ -11,8 +11,7 @@
         from genomicarray import GenomicArrayDataset
 
         garr = GenomicArrayDataset(dataset_path="/path/to/genomicarray/dir")
-        feature_indices = 1:10
-        result1 = garr[feature_indices, 0]
+        result1 = garr[0:10, 0]
 
         print(result1)
 """

src/genomicarrays/GenomicArrayDatasetSlice.py

@@ -11,7 +11,7 @@
         from genomicarray import GenomicArrayDataset
 
         garr = GenomicArrayDataset(dataset_path="/path/to/genomicarray/dir")
-        feature_indices = slice(1, 10)
+        feature_indices = slice(0, 10)
         result1 = garr[feature_indices, 0]
 
         print(result1)

src/genomicarrays/build_genomicarray.py

@@ -20,8 +20,15 @@
         # or just provide the path
         bw2 = "path/to/object2.bw"
 
+        features = pd.DataFrame({
+            "seqnames": ["chr1", "chr1"],
+            "starts": [1000, 2000],
+            "ends": [1500, 2500]
+        })
+
         # Build GenomicArray
         dataset = build_genomicarray(
+            features=features
             output_path=tempdir,
             files=[bw1, bw2],
             matrix_options=MatrixOptions(dtype=np.float32),